+publisher:"University of Texas – Austin" +contributor:("Kutanoglu, Erhan")

University of Texas – Austin

1. -7966-6347. Constraint sensitivity analysis of airline crew rostering using preferential bidding.

Degree: MSin Engineering, Operations Research & Industrial Engineering, 2018, University of Texas – Austin

► Airline crew rostering is an important part of airline operations that can save costs by optimized assignments of crew members to existing sequence of flights… (more)

Subjects/Keywords: Airline crew scheduling; Airline crew rostering; Preferential bidding; Sensitivity analysis

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APA (6^th Edition):

-7966-6347. (2018). Constraint sensitivity analysis of airline crew rostering using preferential bidding. (Masters Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/68913

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Chicago Manual of Style (16^th Edition):

-7966-6347. “Constraint sensitivity analysis of airline crew rostering using preferential bidding.” 2018. Masters Thesis, University of Texas – Austin. Accessed January 24, 2021. http://hdl.handle.net/2152/68913.

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MLA Handbook (7^th Edition):

-7966-6347. “Constraint sensitivity analysis of airline crew rostering using preferential bidding.” 2018. Web. 24 Jan 2021.

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Vancouver:

-7966-6347. Constraint sensitivity analysis of airline crew rostering using preferential bidding. [Internet] [Masters thesis]. University of Texas – Austin; 2018. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/2152/68913.

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Council of Science Editors:

-7966-6347. Constraint sensitivity analysis of airline crew rostering using preferential bidding. [Masters Thesis]. University of Texas – Austin; 2018. Available from: http://hdl.handle.net/2152/68913

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University of Texas – Austin

2. -8796-5224. A framework to measure the value of IoT in spare parts logistics networks.

Degree: MSin Engineering, Operations Research & Industrial Engineering, 2017, University of Texas – Austin

URL: http://hdl.handle.net/2152/67270

► With increasing connectivity and declining data processing costs day-by-day, industrial systems hold a promising future in the wake of technologies like Internet of Things (IoT).… (more)

Subjects/Keywords: Internet of Things; Spare parts logistics; Predictive maintenance; Smart maintenance

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APA (6^th Edition):

-8796-5224. (2017). A framework to measure the value of IoT in spare parts logistics networks. (Masters Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/67270

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Chicago Manual of Style (16^th Edition):

-8796-5224. “A framework to measure the value of IoT in spare parts logistics networks.” 2017. Masters Thesis, University of Texas – Austin. Accessed January 24, 2021. http://hdl.handle.net/2152/67270.

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MLA Handbook (7^th Edition):

-8796-5224. “A framework to measure the value of IoT in spare parts logistics networks.” 2017. Web. 24 Jan 2021.

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Vancouver:

-8796-5224. A framework to measure the value of IoT in spare parts logistics networks. [Internet] [Masters thesis]. University of Texas – Austin; 2017. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/2152/67270.

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Council of Science Editors:

-8796-5224. A framework to measure the value of IoT in spare parts logistics networks. [Masters Thesis]. University of Texas – Austin; 2017. Available from: http://hdl.handle.net/2152/67270

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University of Texas – Austin

3. Liao, Melody. A numerical study of single-machine multiple-recipe predictive maintenance.

Degree: MSin Engineering, Operations Research and Industrial Engineering, 2011, University of Texas – Austin

URL: http://hdl.handle.net/2152/ETD-UT-2011-05-3320

► Effective machine maintenance policy is a critical element of a smooth running manufacturing system. This paper evaluates a multiple-recipe predictive maintenance problem modeled using a… (more)

Subjects/Keywords: Machine maintenance; Maintenance policy; Predictive maintenance

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APA (6^th Edition):

Liao, M. (2011). A numerical study of single-machine multiple-recipe predictive maintenance. (Masters Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2011-05-3320

Chicago Manual of Style (16^th Edition):

Liao, Melody. “A numerical study of single-machine multiple-recipe predictive maintenance.” 2011. Masters Thesis, University of Texas – Austin. Accessed January 24, 2021. http://hdl.handle.net/2152/ETD-UT-2011-05-3320.

MLA Handbook (7^th Edition):

Liao, Melody. “A numerical study of single-machine multiple-recipe predictive maintenance.” 2011. Web. 24 Jan 2021.

Vancouver:

Liao M. A numerical study of single-machine multiple-recipe predictive maintenance. [Internet] [Masters thesis]. University of Texas – Austin; 2011. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/2152/ETD-UT-2011-05-3320.

Council of Science Editors:

Liao M. A numerical study of single-machine multiple-recipe predictive maintenance. [Masters Thesis]. University of Texas – Austin; 2011. Available from: http://hdl.handle.net/2152/ETD-UT-2011-05-3320

University of Texas – Austin

4. McFarland, Ian Christopher. Demand forecasting for job order products in highly technological and emerging industries.

Degree: MSin Engineering, Operations Research and Industrial Engineering, 2012, University of Texas – Austin

URL: http://hdl.handle.net/2152/ETD-UT-2012-05-5514

► Demand forecasting is an important step of a company’s supply chain management process, allowing companies to project their needs for different components that are used… (more)

Subjects/Keywords: Demand forecasting; Supply chain

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APA (6^th Edition):

McFarland, I. C. (2012). Demand forecasting for job order products in highly technological and emerging industries. (Masters Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2012-05-5514

Chicago Manual of Style (16^th Edition):

McFarland, Ian Christopher. “Demand forecasting for job order products in highly technological and emerging industries.” 2012. Masters Thesis, University of Texas – Austin. Accessed January 24, 2021. http://hdl.handle.net/2152/ETD-UT-2012-05-5514.

MLA Handbook (7^th Edition):

McFarland, Ian Christopher. “Demand forecasting for job order products in highly technological and emerging industries.” 2012. Web. 24 Jan 2021.

Vancouver:

McFarland IC. Demand forecasting for job order products in highly technological and emerging industries. [Internet] [Masters thesis]. University of Texas – Austin; 2012. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/2152/ETD-UT-2012-05-5514.

Council of Science Editors:

McFarland IC. Demand forecasting for job order products in highly technological and emerging industries. [Masters Thesis]. University of Texas – Austin; 2012. Available from: http://hdl.handle.net/2152/ETD-UT-2012-05-5514

5. -7369-6828. A comparative analysis of flight crew vacation allocation models.

Degree: MSin Engineering, Operations Research & Industrial Engineering, 2019, University of Texas – Austin

URL: http://dx.doi.org/10.26153/tsw/5679

► The airline industry has a long lasting history of using operations research for complex problems like crew scheduling, crew pairing, and aircraft tail assignment. However,… (more)

Subjects/Keywords: Vacation scheduling; Flight crew vacation scheduling; Mixed integer programming; Numerical analysis

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APA (6^th Edition):

-7369-6828. (2019). A comparative analysis of flight crew vacation allocation models. (Masters Thesis). University of Texas – Austin. Retrieved from http://dx.doi.org/10.26153/tsw/5679

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Chicago Manual of Style (16^th Edition):

-7369-6828. “A comparative analysis of flight crew vacation allocation models.” 2019. Masters Thesis, University of Texas – Austin. Accessed January 24, 2021. http://dx.doi.org/10.26153/tsw/5679.

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MLA Handbook (7^th Edition):

-7369-6828. “A comparative analysis of flight crew vacation allocation models.” 2019. Web. 24 Jan 2021.

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Vancouver:

-7369-6828. A comparative analysis of flight crew vacation allocation models. [Internet] [Masters thesis]. University of Texas – Austin; 2019. [cited 2021 Jan 24]. Available from: http://dx.doi.org/10.26153/tsw/5679.

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Council of Science Editors:

-7369-6828. A comparative analysis of flight crew vacation allocation models. [Masters Thesis]. University of Texas – Austin; 2019. Available from: http://dx.doi.org/10.26153/tsw/5679

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6. Jeet, Vishv. Logistics network design with inventory stocking, time-based service and part commonality.

Degree: PhD, Operations Research and Industrial Engineering, 2006, University of Texas – Austin

URL: http://hdl.handle.net/2152/3400

Subjects/Keywords: Business logistics – Mathematical models

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APA (6^th Edition):

Jeet, V. (2006). Logistics network design with inventory stocking, time-based service and part commonality. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/3400

Chicago Manual of Style (16^th Edition):

Jeet, Vishv. “Logistics network design with inventory stocking, time-based service and part commonality.” 2006. Doctoral Dissertation, University of Texas – Austin. Accessed January 24, 2021. http://hdl.handle.net/2152/3400.

MLA Handbook (7^th Edition):

Jeet, Vishv. “Logistics network design with inventory stocking, time-based service and part commonality.” 2006. Web. 24 Jan 2021.

Vancouver:

Jeet V. Logistics network design with inventory stocking, time-based service and part commonality. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2006. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/2152/3400.

Council of Science Editors:

Jeet V. Logistics network design with inventory stocking, time-based service and part commonality. [Doctoral Dissertation]. University of Texas – Austin; 2006. Available from: http://hdl.handle.net/2152/3400

University of Texas – Austin

7. -3292-7049. Joint maintenance and production operations decision making in flexible manufacturing systems.

Degree: PhD, Operations research and industrial engineering, 2016, University of Texas – Austin

URL: http://hdl.handle.net/2152/46237

► In highly flexible and highly integrated manufacturing systems such as semiconductor manufacturing, equipment has the capability of conducting different manufacturing operations and/or producing at various… (more)

▼ In highly flexible and highly integrated manufacturing systems such as semiconductor manufacturing, equipment has the capability of conducting different manufacturing operations and/or producing at various speeds. In such systems, degradation of a machine depends highly on the operations performed on it. Selection of operations executed on an equipment changes the degradation dynamics and hence directly affects preventive maintenance (PM) decisions. On the other hand, PM actions interrupt production and change the system reliability and equipment availability, which in turn directly affects decisions as to which operations should be performed on which piece of equipment. These strong dynamic interactions between equipment condition, operations executed on the equipment and product quality necessitate a methodology that integrates the decisions of maintenance scheduling and production operations. Currently, maintenance and production operations decision-making are two decoupled processes. To address the aforementioned problems, in this dissertation, we devise integrated decision-making policies for maintenance scheduling and production operations in flexible manufacturing systems (FMS) optimizing a customizable objective function that takes into account operation-dependent degradation models and production targets. The objective function consists of costs associated with scheduled and unscheduled maintenance, rewards for successfully completed products and penalties for missed production targets. In order to maximize the objective function, a paradigm based on metaheuristic optimization and evaluation of candidate solutions via discrete-event simulations of operations of the underlying manufacturing system is used. Firstly, we propose an operation-dependent decision-making policy for a multiple-product/multiple-equipment manufacturing system, where each product requires several operations for completion and the sequence in which different product types are produced is a priori given. The proposed method is tested in simulations of a cluster tool and the results show that operation-dependent maintenance decision-making outperforms the case where maintenance decisions are made without considerations of operation-dependent degradation dynamics. Secondly, we propose an integrated decision-making policy for maintenance scheduling and product sequencing where the sequence in which different product types can be arranged in a way to maximize the customizable profit function. The results show that jointly making maintenance and production sequencing decisions consistently and often significantly outperforms the current practice of making these decisions separately. Finally, a joint maintenance scheduling and production operations decision making policy is proposed for a flexible manufacturing system where the degradation states of the equipment are not perfectly observable, but are rather hidden states of a known Hidden Markov Model (HMM). Proposed integrated decision-making policy under imperfect degradation state… Advisors/Committee Members: Djurdjanovic, Dragan (advisor), Chen, Frank (committee member), Hasenbein, John J (committee member), Kutanoglu, Erhan (committee member), Morton, David P (committee member).

Subjects/Keywords: Maintenance decision making; Product sequencing; Concurrent maintenance & operation decision making; POMDP; Imperfect observation

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APA (6^th Edition):

-3292-7049. (2016). Joint maintenance and production operations decision making in flexible manufacturing systems. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/46237

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Chicago Manual of Style (16^th Edition):

-3292-7049. “Joint maintenance and production operations decision making in flexible manufacturing systems.” 2016. Doctoral Dissertation, University of Texas – Austin. Accessed January 24, 2021. http://hdl.handle.net/2152/46237.

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MLA Handbook (7^th Edition):

-3292-7049. “Joint maintenance and production operations decision making in flexible manufacturing systems.” 2016. Web. 24 Jan 2021.

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Vancouver:

-3292-7049. Joint maintenance and production operations decision making in flexible manufacturing systems. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2016. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/2152/46237.

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Council of Science Editors:

-3292-7049. Joint maintenance and production operations decision making in flexible manufacturing systems. [Doctoral Dissertation]. University of Texas – Austin; 2016. Available from: http://hdl.handle.net/2152/46237

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University of Texas – Austin

8. -1709-7032. Resource allocation in service and logistics systems.

Degree: PhD, Operations Research & Industrial Engineering, 2016, University of Texas – Austin

URL: http://hdl.handle.net/2152/47042

► Resource allocation is a problem commonly encountered in strategic planning, where a typical objective is to minimize the associated cost or maximize the resulting profit.… (more)

▼ Resource allocation is a problem commonly encountered in strategic planning, where a typical objective is to minimize the associated cost or maximize the resulting profit. It is studied analytically and numerically for service and logistics systems in this dissertation, with the major resource being people, services or trucks. First, a staffing level problem is analyzed for large-scale single-station queueing systems. The system manager operates an Erlang-C queueing system with a quality-of-service (QoS) constraint on the probability that a customer is queued. However, in this model, the arrival rate is uncertain in the sense that even the arrival-rate distribution is not completely known to the manager. Rather, the manager has an estimate of the support of the arrival-rate distribution and the mean. The goal is to determine the number of servers needed to satisfy the quality of service constraint. Two models are explored. First, the constraint is enforced on an overall delay probability, given the probability that different feasible arrival-rate distributions are selected. In the second case, the constraint has to be satisfied by every possible distribution. For both problems, asymptotically optimal solutions are developed based on Halfin-Whitt type scalings. The work is followed by a discussion on solution uniqueness with a joint QoS constraint and a given arrival-rate distribution in multi-station systems. Second, an extension to Naor’s analysis on the joining or balking problem in observable M=M=1 queues and its variant in unobservable M=M=1 queues is presented to incorporate parameter uncertainty. The arrival-rate distribution is known to all, but the exact arrival rate is unknown in both cases. The optimal joining strategies are obtained and compared from the perspectives of individual customers, the social optimizer and the profit maximizer, where differences are recognized between the results for systems with deterministic and stochastic arrival rates. Finally, an integrated ordering and inbound shipping problem is formulated for an assembly plant with a large number of suppliers. The objective is to minimize the annual total cost with a static strategy. Potential transportation modes include full truckload shipping and less than truckload shipping, the former of which allows customized routing while the latter does not. A location-based model is applied in search of near-optimal solutions instead of an exact model with vehicle routing, and numerical experiments are conducted to investigate the insights of the problem. Advisors/Committee Members: Hasenbein, John J. (advisor), Kutanoglu, Erhan (advisor), Bickel, James E. (committee member), Khajavirad, Aida (committee member), Morrice, Douglas J. (committee member).

Subjects/Keywords: Staffing service systems; Parameter uncertainty; Game-theoretic queueing; Inbound shipping

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APA (6^th Edition):

-1709-7032. (2016). Resource allocation in service and logistics systems. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/47042

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Chicago Manual of Style (16^th Edition):

-1709-7032. “Resource allocation in service and logistics systems.” 2016. Doctoral Dissertation, University of Texas – Austin. Accessed January 24, 2021. http://hdl.handle.net/2152/47042.

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MLA Handbook (7^th Edition):

-1709-7032. “Resource allocation in service and logistics systems.” 2016. Web. 24 Jan 2021.

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Vancouver:

-1709-7032. Resource allocation in service and logistics systems. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2016. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/2152/47042.

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Council of Science Editors:

-1709-7032. Resource allocation in service and logistics systems. [Doctoral Dissertation]. University of Texas – Austin; 2016. Available from: http://hdl.handle.net/2152/47042

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University of Texas – Austin

9. -9242-5353. Applications of network optimization in cybersecurity and service parts logistics.

Degree: PhD, Operations Research and Industrial Engineering, 2019, University of Texas – Austin

URL: http://dx.doi.org/10.26153/tsw/3008

► We develop and analyze novel network-based optimization models for two very important network-related applications: cybersecurity and service parts logistics. We consider one cybersecurity network problem… (more)

▼ We develop and analyze novel network-based optimization models for two very important network-related applications: cybersecurity and service parts logistics. We consider one cybersecurity network problem and two service parts logistics network problems. The goal is to find tractable solutions to all three problems by creating carefully designed network-based models. The first problem we consider involves decision making in a cybersecurity environment. The goal here is to find the optimal locations to place defensive investments in a cyber physical system so that the probability of being compromised by a persistent attacker is minimized. We use Markov Decision Processes (MDPs) to show that the problem involves stochastic decision making, and we approach it using a network interdiction model. Initially, we create an MDP to come up with a description of a cyber physical network and try to find the optimal attack strategy for a persistent hacker. We show that the results of our MDP model are the same as those of the so called s-t reliability problem, a well-studiedP network problem. To tackle the exponential increase in the state space and the calculation time of the MDP with respect to the size of the cyber physical network, we create a mixed integer program (MIP) to come up with an attacker’s strategy, and develop it further to include a defender by creating a network interdiction model. We show that the results coming from the MIP and MDP model are the same, thus providing a tractable solution to the cybersecurity problem as well as the related s-t reliability problem. The second problem we consider involves decision making in a Service Parts Logistics (SPL) problem. Modifying the traditional assumption of failure based replacements in post-sales service models, we incorporate Condition Based Replacement (CBR) policies into SPL. We utilize the Internet of Things (IoT) and sensors to operationalize the continuous monitoring of the conditions of the parts in the network. We create a model to decide on strategic network design and spare parts stocking, as well as the customer to network facility allocations. Despite the focused work on high value, low demand logistics models such as SPL in the literature, there has not been a study of integrated SPL problems involving CBR policies. Along with the facility location, customer-to-facility allocation and part stock level decisions for given fill-rate based service levels, the CBR-extended SPL model also finds the optimal conditions to replace the parts at each customer. After a careful development of the part degradation process using a Continuous Time Markov Chain model, we incorporate the CBR policies into the integrated SPL model, which turns out to be a Mixed Integer Program with Quadratic Constraints (MIQCP). Our results show that the CBR flexibility brings in significant savings in the objective function (total costs of the network) when compared to the optimal solutions of the failure-based replacement (FBR) policies. Moreover, in almost all problem instances under a… Advisors/Committee Members: Kutanoglu, Erhan (advisor), Hanasusanto, Grani A (committee member), Hasenbein, John J (committee member), Iyoob, Ilyas (committee member).

Subjects/Keywords: Network optimization; Cybersecurity; Service parts logistics; Condition based replacement; Additive manufacturing; Integer programming; Mixed integer programming with quadratic constraints; Markov Decision Processes

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APA (6^th Edition):

-9242-5353. (2019). Applications of network optimization in cybersecurity and service parts logistics. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://dx.doi.org/10.26153/tsw/3008

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Chicago Manual of Style (16^th Edition):

-9242-5353. “Applications of network optimization in cybersecurity and service parts logistics.” 2019. Doctoral Dissertation, University of Texas – Austin. Accessed January 24, 2021. http://dx.doi.org/10.26153/tsw/3008.

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MLA Handbook (7^th Edition):

-9242-5353. “Applications of network optimization in cybersecurity and service parts logistics.” 2019. Web. 24 Jan 2021.

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Vancouver:

-9242-5353. Applications of network optimization in cybersecurity and service parts logistics. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2019. [cited 2021 Jan 24]. Available from: http://dx.doi.org/10.26153/tsw/3008.

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Council of Science Editors:

-9242-5353. Applications of network optimization in cybersecurity and service parts logistics. [Doctoral Dissertation]. University of Texas – Austin; 2019. Available from: http://dx.doi.org/10.26153/tsw/3008

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University of Texas – Austin

10. -2430-3116. Integrated decision-making framework for preventive maintenance scheduling and spare part logistic planning.

Degree: PhD, Operations Research and Industrial Engineering, 2018, University of Texas – Austin

URL: http://hdl.handle.net/2152/63737

► Maintenance scheduling for geographically distributed assets intricately and closely depends on the locations and availability of spare parts, which motivates the joint decision-making on the… (more)

▼ Maintenance scheduling for geographically distributed assets intricately and closely depends on the locations and availability of spare parts, which motivates the joint decision-making on the maintenance scheduling and spare part logistics, including optimization of the system operations, as well as the design of the underlying spare part logistic network. These close interactions between the maintenance and spare part logistic activities have been ignored or oversimplified in the existing research and practice, leading to the inappropriate maintenance resource allocations and excessive maintenance waiting times. Unfortunately, such kind of joint decision-making problems are challenging due to the exceptionally large size of the decision space, as well as the strong inter-dependencies in the system operations, especially for large-scale systems with complex maintenance/logistic structures. Challenges become even more pronounced if one acknowledges that those system operations and degradation processes of the assets are greatly influenced by numerous uncertain factors, yielding highly stochastic system behaviors. To address the aforementioned problems and challenges, in this doctoral dissertation, an integrated decision-making framework is proposed to effectively schedule preventive maintenance (PM) for geographically distributed assets and properly manage inventories in distributed logistic facilities storing the necessary spare parts. In addition, several factors are discussed within the proposed decision-making framework, including the inventory-sharing structure, imperfect maintenance, transportation options and spare parts logistic network design. To capture the stochastic nature of the system operations and the trade-offs between decisions in the domains of maintenance scheduling, spare part inventory management, transportation selection and logistic network construction, a discrete-event simulation-based optimization paradigm was used to minimize generic and customizable cost functions, that reward functioning of the assets, while penalizing asset downtime and consumptions of maintenance/logistic resources. The benefits of the newly proposed integrated decision-making framework are illustrated in simulations, through comparisons between the integrated policies with several traditional, fragmented decision-making processes. Moreover, a design of experiment (DOE) based sensitivity analysis is introduced to evaluate the effects of a variety of relevant systems parameters on the resulting system operations. Future work should be aimed at incorporating robustness to uncertainties in model structures and system parameters into the newly proposed decision-making and system design methodologies, as well as implementing these methods in a real-life system settings, rather than simulations alone. Advisors/Committee Members: Djurdjanovic, Dragan (advisor), Hanasusanto, Grani (committee member), Kutanoglu, Erhan (committee member), Michalopoulos, Dennis (committee member), Jin, Xiaoning (committee member).

Subjects/Keywords: Optimization; Spare part logistics; Preventive maintenance

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APA (6^th Edition):

-2430-3116. (2018). Integrated decision-making framework for preventive maintenance scheduling and spare part logistic planning. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/63737

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Chicago Manual of Style (16^th Edition):

-2430-3116. “Integrated decision-making framework for preventive maintenance scheduling and spare part logistic planning.” 2018. Doctoral Dissertation, University of Texas – Austin. Accessed January 24, 2021. http://hdl.handle.net/2152/63737.

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MLA Handbook (7^th Edition):

-2430-3116. “Integrated decision-making framework for preventive maintenance scheduling and spare part logistic planning.” 2018. Web. 24 Jan 2021.

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Vancouver:

-2430-3116. Integrated decision-making framework for preventive maintenance scheduling and spare part logistic planning. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2018. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/2152/63737.

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Council of Science Editors:

-2430-3116. Integrated decision-making framework for preventive maintenance scheduling and spare part logistic planning. [Doctoral Dissertation]. University of Texas – Austin; 2018. Available from: http://hdl.handle.net/2152/63737

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11. Huang, Hsin-Chan. Stockpiling and resource allocation for influenza preparedness and manufacturing assembly.

Degree: PhD, Operations Research and Industrial Engineering, 2014, University of Texas – Austin

URL: http://hdl.handle.net/2152/27150

► Stockpiling resources is a pervasive way to handle demand uncertainty and future demand surges. However, stockpiling is subject to costs, including warehousing costs, inventory holding… (more)

▼ Stockpiling resources is a pervasive way to handle demand uncertainty and future demand surges. However, stockpiling is subject to costs, including warehousing costs, inventory holding costs, and wastage of expired resources. Hence, how to stockpile in an economically efficient manner is an important topic to study. Furthermore, if the inventoried supply is insufficient for a surge in demand, how to best allocate available resources becomes a natural question to ask. In this dissertation, we consider three applications of stockpiling and resource allocation: (i) we stockpile ventilators both centrally and regionally for an influenza pandemic; (ii) we allocate limited vaccine doses of various types to target populations for an influenza pandemic; and, (iii) we investigate inventory needs for low cost, high usage (class C) parts in an engine assembly plant. First, we describe and analyze a model for estimating the number of ventilators that the Texas Department of State Health Services (DSHS), and eight health service regions in Texas, should stockpile for an influenza pandemic. Using a probability distribution governing peak-week demand for ventilators across the eight health service regions, an optimization model allows investigation of the tradeoff between the cost of the total stockpile and the expected shortfall of ventilators under mild, moderate, and severe pandemic scenarios. Our analysis yields the surprising result that there is little benefit to DSHS holding a significant stockpile, even when those centrally held ventilators can be dispatched to regions after observing the peak-week demand realization. Three factors contribute to this result: positively correlated regional demands, a relatively low coefficient of variation, and wastage of the central stockpile once it is dispatched to the regions. Second, we formulate an optimization model for allocating various types of vaccines to multiple priority groups in 254 counties in the state of Texas that DSHS can use to distribute its vaccines for an influenza pandemic. For reaching the public, vaccines are allocated to the state’s Registered Providers (RPs), Local Health Departments (LHDs), and Health Service Regions (HSRs). The first two allocations are driven by requests from RPs and LHDs while HSR allocation is at DSHS’s discretion. The optimization model aims to achieve proportionally fair coverage of priority groups across the 254 counties, as informed by user-specified weights on those priority groups, using the HSR doses. With proportional fairness as our primary goal, the optimal allocation also counts policy simplicity and regional equity. Sensitivity analysis on the portion of the state’s vaccines reserved for HSRs shows that a small portion can effectively shrink the gap of vaccination coverage between urban and rural counties. Finally, we derive short-cut formulae for estimating the extra inventory needed for managing class C parts in units of bins that an engine assembly plant can use to achieve a desired fill rate at workstations. The plant orders… Advisors/Committee Members: Morton, David P. (advisor), Kutanoglu, Erhan (advisor).

Subjects/Keywords: Ventilator stockpiling; Vaccine allocation; Bin delivery effect; Optimization; Influenza preparedness; Manufacturing assembly

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APA (6^th Edition):

Huang, H. (2014). Stockpiling and resource allocation for influenza preparedness and manufacturing assembly. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/27150

Chicago Manual of Style (16^th Edition):

Huang, Hsin-Chan. “Stockpiling and resource allocation for influenza preparedness and manufacturing assembly.” 2014. Doctoral Dissertation, University of Texas – Austin. Accessed January 24, 2021. http://hdl.handle.net/2152/27150.

MLA Handbook (7^th Edition):

Huang, Hsin-Chan. “Stockpiling and resource allocation for influenza preparedness and manufacturing assembly.” 2014. Web. 24 Jan 2021.

Vancouver:

Huang H. Stockpiling and resource allocation for influenza preparedness and manufacturing assembly. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2014. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/2152/27150.

Council of Science Editors:

Huang H. Stockpiling and resource allocation for influenza preparedness and manufacturing assembly. [Doctoral Dissertation]. University of Texas – Austin; 2014. Available from: http://hdl.handle.net/2152/27150

12. Cai, Yiwei. Semiconductor manufacturing inspired integrated scheduling problems : production planning, advanced process control, and predictive maintenance.

Degree: PhD, Operations Research and Industrial Engineering, 2008, University of Texas – Austin

URL: http://hdl.handle.net/2152/17950

► This dissertation is composed of three major parts, each studying a problem related to semiconductor manufacturing. The first part of the dissertation proposes a high-level… (more)

▼ This dissertation is composed of three major parts, each studying a problem related to semiconductor manufacturing. The first part of the dissertation proposes a high-level scheduling model that serves as an intermediate stage between planning and detailed scheduling in the usual planning hierarchy. The high-level scheduling model explicitly controls the WIP over time in the system and provides a more specific guide to detailed scheduling. WIP control is used to balance the WIP (Work In Process) level and to keep the bottleneck station busy to maintain a high throughput rate. A mini-fab simulation model is used to evaluate the benefits of different approaches to implementing such a high-level scheduling model, and to compare different WIP control policies. Extensive numerical studies show that the proposed approaches can achieve much shorter cycle times than the traditional planning-scheduling approach, with only a small increase in inventory and backorder costs. With increasing worldwide competition, high technology product manufacturing companies have to pay great attention to lower their production costs and guarantee high quality at the same time. Advanced process control (APC) is widely used in semiconductor manufacturing to adjust machine parameters so as to achieve satisfactory product quality. The interaction between scheduling and APC motivates the second part of this dissertation. First, a single-machine makespan problem with APC constraints is proved to be NPcomplete. For some special cases, an optimal solution is obtained analytically. In more general cases, the structure of optimal solutions is explored. An efficient heuristic algorithm based on these structural results is proposed and compared to an integer programming approach. Another important issue in manufacturing system is maintenance, which affects cycle time and yield management. Although there is extensive literature regarding maintenance policies, the analysis in most papers is restricted to conventional preventive maintenance (PM) policies, i.e., calendar-based or jobbased PM policies. With the rapid development of new technology, predictive maintenance has become more feasible, and has attracted more and more attention from semiconductor manufacturing companies in recent years. Thus, the third problem considered in this dissertation is predictive maintenance in an M/G/1 queueing environment. One-recipe and two-recipe problems are studied through semi-Markov decision processes (SMDP), and structural properties are obtained. Discounted SMDP problems are solved by linear programming and expected machine availabilities are calculated to evaluate different PM policies. The optimal policy can maintain a high machine availability with low long-run cost. The structures of the optimal PM policies show that it is necessary to consider multiple recipes explicitly in predictive maintenance models. Advisors/Committee Members: Kutanoglu, Erhan (advisor), Qin, Sizhao (advisor).

Subjects/Keywords: Semiconductor industry – Production control – Mathematical models; Semiconductor industry – Production control – Mathematics; Process control – Mathematical models; Process control – Mathematics; Maintenance; Semiconductors – Design and construction – Mathematics

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APA (6^th Edition):

Cai, Y. (2008). Semiconductor manufacturing inspired integrated scheduling problems : production planning, advanced process control, and predictive maintenance. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/17950

Chicago Manual of Style (16^th Edition):

Cai, Yiwei. “Semiconductor manufacturing inspired integrated scheduling problems : production planning, advanced process control, and predictive maintenance.” 2008. Doctoral Dissertation, University of Texas – Austin. Accessed January 24, 2021. http://hdl.handle.net/2152/17950.

MLA Handbook (7^th Edition):

Cai, Yiwei. “Semiconductor manufacturing inspired integrated scheduling problems : production planning, advanced process control, and predictive maintenance.” 2008. Web. 24 Jan 2021.

Vancouver:

Cai Y. Semiconductor manufacturing inspired integrated scheduling problems : production planning, advanced process control, and predictive maintenance. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2008. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/2152/17950.

Council of Science Editors:

Cai Y. Semiconductor manufacturing inspired integrated scheduling problems : production planning, advanced process control, and predictive maintenance. [Doctoral Dissertation]. University of Texas – Austin; 2008. Available from: http://hdl.handle.net/2152/17950

13. Poladi, Ranjith. Automated assembly sequence generation using a novel search scheme for handling parallel sub-assemblies.

Degree: MSin Engineering, Operations Research and Industrial Engineering, 2013, University of Texas – Austin

URL: http://hdl.handle.net/2152/22387

► The Assembly sequencing problem (ASP) is part of the assembly planning process. The ASP is basically a large scale, combinatorial problem which is highly constrianed.… (more)

Subjects/Keywords: Assembly sequencing; Tree search; ASP

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APA (6^th Edition):

Poladi, R. (2013). Automated assembly sequence generation using a novel search scheme for handling parallel sub-assemblies. (Masters Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/22387

Chicago Manual of Style (16^th Edition):

Poladi, Ranjith. “Automated assembly sequence generation using a novel search scheme for handling parallel sub-assemblies.” 2013. Masters Thesis, University of Texas – Austin. Accessed January 24, 2021. http://hdl.handle.net/2152/22387.

MLA Handbook (7^th Edition):

Poladi, Ranjith. “Automated assembly sequence generation using a novel search scheme for handling parallel sub-assemblies.” 2013. Web. 24 Jan 2021.

Vancouver:

Poladi R. Automated assembly sequence generation using a novel search scheme for handling parallel sub-assemblies. [Internet] [Masters thesis]. University of Texas – Austin; 2013. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/2152/22387.

Council of Science Editors:

Poladi R. Automated assembly sequence generation using a novel search scheme for handling parallel sub-assemblies. [Masters Thesis]. University of Texas – Austin; 2013. Available from: http://hdl.handle.net/2152/22387

14. Varghese, Libin Koshy. Study of a share based passenger mix model.

Degree: MSin Engineering, Operations Research and Industrial Engineering, 2012, University of Texas – Austin

URL: http://hdl.handle.net/2152/ETD-UT-2012-05-5571

► A passenger mix model (PMM) is used by airlines to find out how many passengers will fly on a fleet schedule. There are numerous ways… (more)

Subjects/Keywords: Passenger mix model

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APA (6^th Edition):

Varghese, L. K. (2012). Study of a share based passenger mix model. (Masters Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2012-05-5571

Chicago Manual of Style (16^th Edition):

Varghese, Libin Koshy. “Study of a share based passenger mix model.” 2012. Masters Thesis, University of Texas – Austin. Accessed January 24, 2021. http://hdl.handle.net/2152/ETD-UT-2012-05-5571.

MLA Handbook (7^th Edition):

Varghese, Libin Koshy. “Study of a share based passenger mix model.” 2012. Web. 24 Jan 2021.

Vancouver:

Varghese LK. Study of a share based passenger mix model. [Internet] [Masters thesis]. University of Texas – Austin; 2012. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/2152/ETD-UT-2012-05-5571.

Council of Science Editors:

Varghese LK. Study of a share based passenger mix model. [Masters Thesis]. University of Texas – Austin; 2012. Available from: http://hdl.handle.net/2152/ETD-UT-2012-05-5571

15. Shen, Yue, master of science in engineering. Amusement park visitor routes design and optimization.

Degree: MSin Engineering, Operations Research and Industrial Engineering, 2012, University of Texas – Austin

URL: http://hdl.handle.net/2152/ETD-UT-2012-05-5652

► Amusement parks are a huge business. Guest experiences determine the success or failure for an amusement park. This report suggests an approach to improve guest… (more)

Subjects/Keywords: Amusement park operations; Visitor routes management; Two-phase heuristics; Attraction simulation; Queue waiting time; Route construction algorithm; Mixed integer programming

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APA (6^th Edition):

Shen, Yue, m. o. s. i. e. (2012). Amusement park visitor routes design and optimization. (Masters Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2012-05-5652

Chicago Manual of Style (16^th Edition):

Shen, Yue, master of science in engineering. “Amusement park visitor routes design and optimization.” 2012. Masters Thesis, University of Texas – Austin. Accessed January 24, 2021. http://hdl.handle.net/2152/ETD-UT-2012-05-5652.

MLA Handbook (7^th Edition):

Shen, Yue, master of science in engineering. “Amusement park visitor routes design and optimization.” 2012. Web. 24 Jan 2021.

Vancouver:

Shen, Yue mosie. Amusement park visitor routes design and optimization. [Internet] [Masters thesis]. University of Texas – Austin; 2012. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/2152/ETD-UT-2012-05-5652.

Council of Science Editors:

Shen, Yue mosie. Amusement park visitor routes design and optimization. [Masters Thesis]. University of Texas – Austin; 2012. Available from: http://hdl.handle.net/2152/ETD-UT-2012-05-5652

16. Carroll, Benjamin Todd. Relevant factors in the path of successful implementation of Lean.

Degree: MSin Engineering, Engineering Management, 2011, University of Texas – Austin

URL: http://hdl.handle.net/2152/ETD-UT-2011-12-4654

► In any business environment companies experience challenges and competition. In this current worldwide economic crisis, the stakes are now higher. With every crisis comes opportunity.… (more)

Subjects/Keywords: Lean; Product development; Manufacturing; Cost savings; Efficiency; Toyota way; Gemba; Kaizen; Implementation; Successful

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APA (6^th Edition):

Carroll, B. T. (2011). Relevant factors in the path of successful implementation of Lean. (Masters Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2011-12-4654

Chicago Manual of Style (16^th Edition):

Carroll, Benjamin Todd. “Relevant factors in the path of successful implementation of Lean.” 2011. Masters Thesis, University of Texas – Austin. Accessed January 24, 2021. http://hdl.handle.net/2152/ETD-UT-2011-12-4654.

MLA Handbook (7^th Edition):

Carroll, Benjamin Todd. “Relevant factors in the path of successful implementation of Lean.” 2011. Web. 24 Jan 2021.

Vancouver:

Carroll BT. Relevant factors in the path of successful implementation of Lean. [Internet] [Masters thesis]. University of Texas – Austin; 2011. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/2152/ETD-UT-2011-12-4654.

Council of Science Editors:

Carroll BT. Relevant factors in the path of successful implementation of Lean. [Masters Thesis]. University of Texas – Austin; 2011. Available from: http://hdl.handle.net/2152/ETD-UT-2011-12-4654

University of Texas – Austin

17. Candas, Mehmet Ferhat, 1979-. Considering inventory in service parts logistics network design problems with time-based service constraints.

Degree: PhD, Operations Research and Industrial Engineering, 2007, University of Texas – Austin

URL: http://hdl.handle.net/2152/3203

► We study the integrated logistics network design and inventory stocking problem as characterized by the interdependency of design and stocking decisions in service parts logistics.… (more)

▼ We study the integrated logistics network design and inventory stocking problem as characterized by the interdependency of design and stocking decisions in service parts logistics. These two sets of decisions usually have been considered sequentially in practice, and their associated problems have been tackled separately in the research literature. The overall problem is typically further complicated due to time-based service constraints that provide lower limits for the percentages of demand satisfied within specified time windows. We introduce an optimization model that explicitly captures the interdependency between network design (location of facilities, and allocation of demands to facilities) and inventory stocking decisions (stock levels and their corresponding stochastic fill rates), and present computational results from our extensive experiments that investigate the effects of several factors including demand levels, time-based service levels, and costs. Our findings indicate that the integrated approach can provide significant cost savings over the decoupled approach (solving the network design first and inventory stocking next), shifting the whole efficient frontier curve between cost and service level to superior regions. Furthermore, we show that the decoupled and integrated approaches may generate totally different solutions, even in the number of located facilities and in their locations, magnifying the importance of considering inventory as part of the network design models. Our analysis consists of a special case of integrated logistics network design and inventory stocking problem in service parts logistics, where each customer requires a certain time-based service level. Introduced is a non-linear mixed integer optimization model that is beyond our current solution technologies, yet it explicitly captures the interdependency between network design (locating facilities, and allocating customers to facilities) and inventory stocking decisions (stock levels and their corresponding stochastic fill rates). We provide two different linearized mixed integer formulations for this problem that can solve small and medium size instances. We reveal that this problem can be formulated as a capacitated facility location problem with polynomially solvable sub cases. However, it is still a challenging problem for which we have a Lagrangian-relaxation based approach that provides extremely tight lower and upper bounds. By applying the methodology and insights of the customer-centric problem, we succeed in providing upper and lower bounds to the original system-wide service level problem, even with large instances and with medium demand levels. Advisors/Committee Members: Kutanoglu, Erhan (advisor).

Subjects/Keywords: Business logistics

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APA (6^th Edition):

Candas, Mehmet Ferhat, 1. (2007). Considering inventory in service parts logistics network design problems with time-based service constraints. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/3203

Chicago Manual of Style (16^th Edition):

Candas, Mehmet Ferhat, 1979-. “Considering inventory in service parts logistics network design problems with time-based service constraints.” 2007. Doctoral Dissertation, University of Texas – Austin. Accessed January 24, 2021. http://hdl.handle.net/2152/3203.

MLA Handbook (7^th Edition):

Candas, Mehmet Ferhat, 1979-. “Considering inventory in service parts logistics network design problems with time-based service constraints.” 2007. Web. 24 Jan 2021.

Vancouver:

Candas, Mehmet Ferhat 1. Considering inventory in service parts logistics network design problems with time-based service constraints. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2007. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/2152/3203.

Council of Science Editors:

Candas, Mehmet Ferhat 1. Considering inventory in service parts logistics network design problems with time-based service constraints. [Doctoral Dissertation]. University of Texas – Austin; 2007. Available from: http://hdl.handle.net/2152/3203

University of Texas – Austin

18. Iyoob, Ilyas Mohamed, 1984-. Customer dedicated facilities and inventory sharing in integrated network design and inventory optimization.

Degree: PhD, Operations Research and Industrial Engineering, 2007, University of Texas – Austin

URL: http://hdl.handle.net/2152/3256

► Shrinking profit margins in the high technology industry has led companies to attempt to increase profits through an increased focus on after-market services. As part… (more)

▼ Shrinking profit margins in the high technology industry has led companies to attempt to increase profits through an increased focus on after-market services. As part of that effort, service parts logistics, which manages the post-sales distribution of spare parts needed to maintain and repair products in use, has gained importance. In an effort to improve Service Parts Logistics (SPL) operations, we integrate facility location and inventory stocking decisions while classifying facilities based on their assignment; dedicated facilities that are assigned solely to individual customers (located on-site of the customer, serving only that customer), and shared facilities that are assigned to a subset of customers. The introduction of dedicated facilities simplifies the overall problem formulation in certain special cases. In one such special case where there is only one facility and none of the customers are within its service time window, the overall problem reduces to a binary knapsack formulation. This can be solved in pseudo-polynomial time through the dynamic programming algorithm for such problems. Nonetheless, even in the general case, we identify conditions under which a dedicated facility will always be opened. Computational results show that this observation is used by solvers as a preprocessing step, thus loosening some hard constraints. As a result, some of these problems are solved in less time than the corresponding problems without the dedicated facilities. However, dedicated facilities become advantageous mainly in sparse networks as opposed to dense networks. Apart from low network density, low holding cost and relatively high demand are two other system parameters that encourage the opening of dedicated facilities. SPL can be further improved by sharing inventory across shared facilities, which is already a common practice in real SPL systems. In this case, Markov chains can be used to estimate fill rates, but the process is iterative. However, under the low demand assumption of parts in SPL, we derive analytical formulae of estimating fill rates and thus incorporate inventory sharing within the network design and inventory optimization model. Special cases of this problem can be solved by an alternative binary knapsack formulation. Computational results show that large instances can be solved instantaneously, and we also identify a greedy heuristic that provides bounds on average within 0.12% of the optimal solution. We observe maximum benefit from inventory sharing when there exists large demand in the area overlapping the time window of both shared facilities and when inventory replenishment rates are high. However, we also identify conditions on the system parameters where inventory sharing could increase cost and/or decrease service in comparison with not-sharing. The combined problem of inventory sharing with customer dedicated facilities is formulated based on a binary knapsack structure. However, the problem size increases exponentially with solution time. Therefore, we… Advisors/Committee Members: Kutanoglu, Erhan (advisor).

Subjects/Keywords: High technology industries – Inventory control – Mathematical models; High technology industries – Inventory control – Cost control – Mathematical models; High technology industries – Cost control

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APA (6^th Edition):

Iyoob, Ilyas Mohamed, 1. (2007). Customer dedicated facilities and inventory sharing in integrated network design and inventory optimization. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/3256

Chicago Manual of Style (16^th Edition):

Iyoob, Ilyas Mohamed, 1984-. “Customer dedicated facilities and inventory sharing in integrated network design and inventory optimization.” 2007. Doctoral Dissertation, University of Texas – Austin. Accessed January 24, 2021. http://hdl.handle.net/2152/3256.

MLA Handbook (7^th Edition):

Iyoob, Ilyas Mohamed, 1984-. “Customer dedicated facilities and inventory sharing in integrated network design and inventory optimization.” 2007. Web. 24 Jan 2021.

Vancouver:

Iyoob, Ilyas Mohamed 1. Customer dedicated facilities and inventory sharing in integrated network design and inventory optimization. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2007. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/2152/3256.

Council of Science Editors:

Iyoob, Ilyas Mohamed 1. Customer dedicated facilities and inventory sharing in integrated network design and inventory optimization. [Doctoral Dissertation]. University of Texas – Austin; 2007. Available from: http://hdl.handle.net/2152/3256

19. -9365-5003. Dynamic decision making under uncertainty for semiconductor manufacturing and healthcare.

Degree: PhD, Operations Research and Industrial Engineering, 2019, University of Texas – Austin

URL: http://dx.doi.org/10.26153/tsw/2085

► This dissertation proposes multiple methods to improve processes and make better decisions in manufacturing and healthcare. First, it investigates algorithms for controlling the automated material… (more)

▼ This dissertation proposes multiple methods to improve processes and make better decisions in manufacturing and healthcare. First, it investigates algorithms for controlling the automated material handling system (AMHS) in a wafer fab. In particular, this research examines algorithms that route vehicles for both the pickup and delivery of lots, with the goal of improving vehicle flow, cycle time, and avoiding congested segments in the AMHS. The proposed methods are simulated using both a stylized simulation model and a more detailed Automod model. These simulations demonstrate that algorithms designed specifically to anticipate congestion can significantly improve some fab metrics. Secondly, this research develops several algorithms for ranking tools in a manufacturing facility so that routes can be categorized and the best routes can be used for recipe probing. Ranking is performed using three different metrics: score-based metrics where higher implies better, target-based metrics where a balance has to be struck by the decision maker between accuracy and precision of a tool based on a target value, and count based metrics such as defect data where a lower number is better (e.g., zero defects is the best scenario). In this part of the dissertation, the ranking algorithms designed for count based metrics are the main contribution to the tool-ranking literature for the manufacturing industry. Finally, the dissertation addresses the problem of medical decision making under uncertainty during the treatment of epilepsy. Here the sequential decision making problem is modeled as an average cost Markov decision process (MDP) to maximize a patient's remaining quality of life. A crucial issue is the uncertainty in transition probabilities extracted from medical studies in epilepsy due to attrition of patients from studies, lack of data and lack of proper experimental design owing to the complexity in treatment procedure. This is addressed by formulating a robust MDP that suggests the best course of treatment for a patient. Advisors/Committee Members: Hasenbein, John J. (advisor), Clarke, Dave F (committee member), Kutanoglu, Erhan (committee member), Bard, Jonathan F (committee member).

Subjects/Keywords: Semiconductor; Healthcare; Markov decision processes; Average cost Markov decision process; Statistics; Simulation; Count regression; Ranking; Routing; Robust optimization; Robust Markov decision processes; Robust average cost Markov decision process; Medical decision making; Epilepsy

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APA (6^th Edition):

-9365-5003. (2019). Dynamic decision making under uncertainty for semiconductor manufacturing and healthcare. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://dx.doi.org/10.26153/tsw/2085

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Chicago Manual of Style (16^th Edition):

-9365-5003. “Dynamic decision making under uncertainty for semiconductor manufacturing and healthcare.” 2019. Doctoral Dissertation, University of Texas – Austin. Accessed January 24, 2021. http://dx.doi.org/10.26153/tsw/2085.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

MLA Handbook (7^th Edition):

-9365-5003. “Dynamic decision making under uncertainty for semiconductor manufacturing and healthcare.” 2019. Web. 24 Jan 2021.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

-9365-5003. Dynamic decision making under uncertainty for semiconductor manufacturing and healthcare. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2019. [cited 2021 Jan 24]. Available from: http://dx.doi.org/10.26153/tsw/2085.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

-9365-5003. Dynamic decision making under uncertainty for semiconductor manufacturing and healthcare. [Doctoral Dissertation]. University of Texas – Austin; 2019. Available from: http://dx.doi.org/10.26153/tsw/2085

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

20. Martin, Kiel. An advanced tabu search approach to the intratheater airlift operations problem with split loading.

Degree: PhD, Operations Research and Industrial Engineering, 2012, University of Texas – Austin

URL: http://hdl.handle.net/2152/ETD-UT-2012-08-5974

► This dissertation details an algorithm to solve the Intratheater Airlift Operations Problem (IAOP) using advanced tabu search. A solution to the IAOP determines the routes… (more)

Subjects/Keywords: Tabu search; Metaheuristics; Split loads; Pickup and delivery problem with time windows; Capacitated team orienteering problem

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APA (6^th Edition):

Martin, K. (2012). An advanced tabu search approach to the intratheater airlift operations problem with split loading. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2012-08-5974

Chicago Manual of Style (16^th Edition):

Martin, Kiel. “An advanced tabu search approach to the intratheater airlift operations problem with split loading.” 2012. Doctoral Dissertation, University of Texas – Austin. Accessed January 24, 2021. http://hdl.handle.net/2152/ETD-UT-2012-08-5974.

MLA Handbook (7^th Edition):

Martin, Kiel. “An advanced tabu search approach to the intratheater airlift operations problem with split loading.” 2012. Web. 24 Jan 2021.

Vancouver:

Martin K. An advanced tabu search approach to the intratheater airlift operations problem with split loading. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2012. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/2152/ETD-UT-2012-08-5974.

Council of Science Editors:

Martin K. An advanced tabu search approach to the intratheater airlift operations problem with split loading. [Doctoral Dissertation]. University of Texas – Austin; 2012. Available from: http://hdl.handle.net/2152/ETD-UT-2012-08-5974

21. Liang, Ziyu. Variational problems for semi-martingale Reflected Brownian Motion in the octant.

Degree: PhD, Operations Research and Industrial Engineering, 2012, University of Texas – Austin

URL: http://hdl.handle.net/2152/19597

► Understand the behavior of queueing networks in heavy tra c is very important due to its importance in evaluating the network performance in related applications.… (more)

Subjects/Keywords: Reflected Brownian Motions; Large deviations principle; Variational problems

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APA (6^th Edition):

Liang, Z. (2012). Variational problems for semi-martingale Reflected Brownian Motion in the octant. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/19597

Chicago Manual of Style (16^th Edition):

Liang, Ziyu. “Variational problems for semi-martingale Reflected Brownian Motion in the octant.” 2012. Doctoral Dissertation, University of Texas – Austin. Accessed January 24, 2021. http://hdl.handle.net/2152/19597.

MLA Handbook (7^th Edition):

Liang, Ziyu. “Variational problems for semi-martingale Reflected Brownian Motion in the octant.” 2012. Web. 24 Jan 2021.

Vancouver:

Liang Z. Variational problems for semi-martingale Reflected Brownian Motion in the octant. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2012. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/2152/19597.

Council of Science Editors:

Liang Z. Variational problems for semi-martingale Reflected Brownian Motion in the octant. [Doctoral Dissertation]. University of Texas – Austin; 2012. Available from: http://hdl.handle.net/2152/19597

22. Lee, Jinho, doctor of operations research and industrial engineering. Stochastic Optimization Models for Rapid Detection of Viruses in Cellphone Networks.

Degree: PhD, Operations Research and Industrial Engineering, 2012, University of Texas – Austin

URL: http://hdl.handle.net/2152/ETD-UT-2012-08-5924

► We develop a class of models to represent the dynamics of a virus spreading in a cellphone network, employing a taxonomy that includes five key… (more)

▼ We develop a class of models to represent the dynamics of a virus spreading in a cellphone network, employing a taxonomy that includes five key characteristics. Based on the resulting dynamics governing the spread, we present optimization models to rapidly detect the virus, subject to resource limitations. We consider two goals, maximizing the probability of detecting a virus by a time threshold and minimizing the expected time to detection, which can be applied to all spread models we consider. We establish a submodularity result for these two objective functions that ensures that a greedy heuristic yields a well-known constant-factor (63%) approximation. We relate the latter optimization problem, under a specific virus-spread mechanism from our class of models, to a classic facility-location model. Using data from a large carrier, we build several base cellphone contact networks of different scale. We then rescale these base networks using the so-called c-core decomposition that removes vertices of low degree in a recursive way. We further show that this down-sampling strategy preserves, in general, the topological properties of the base networks, based on testing several measures. For the objective that maximizes the probability that we detect a virus by a time threshold, we provide a sample-average optimization model that yields an asymptotically-optimal design for locating the detection devices, as the number of samples grows large. To choose a relevant time threshold, we perform a simulation for some spread models. We then test the performance of our proposed solution methods by solving the presented optimization models for some spread dynamics using some of the contact networks built after the c-core decomposition. The computational results show that the greedy algorithm is an efficient way to solve the corresponding sample-average approximation model, and the greedy solutions outperform some other simple solution approaches. Advisors/Committee Members: Morton, David P. (advisor), Hasenbein, John J. (advisor), Popova, Elmira (committee member), Kutanoglu, Erhan (committee member), Shakkottai, Sanjay (committee member).

Subjects/Keywords: Submodularity; Greedy heuristic; Down-sampling procedure; Monte Carlo approximation

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APA (6^th Edition):

Lee, Jinho, d. o. o. r. a. i. e. (2012). Stochastic Optimization Models for Rapid Detection of Viruses in Cellphone Networks. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2012-08-5924

Chicago Manual of Style (16^th Edition):

Lee, Jinho, doctor of operations research and industrial engineering. “Stochastic Optimization Models for Rapid Detection of Viruses in Cellphone Networks.” 2012. Doctoral Dissertation, University of Texas – Austin. Accessed January 24, 2021. http://hdl.handle.net/2152/ETD-UT-2012-08-5924.

MLA Handbook (7^th Edition):

Lee, Jinho, doctor of operations research and industrial engineering. “Stochastic Optimization Models for Rapid Detection of Viruses in Cellphone Networks.” 2012. Web. 24 Jan 2021.

Vancouver:

Lee, Jinho dooraie. Stochastic Optimization Models for Rapid Detection of Viruses in Cellphone Networks. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2012. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/2152/ETD-UT-2012-08-5924.

Council of Science Editors:

Lee, Jinho dooraie. Stochastic Optimization Models for Rapid Detection of Viruses in Cellphone Networks. [Doctoral Dissertation]. University of Texas – Austin; 2012. Available from: http://hdl.handle.net/2152/ETD-UT-2012-08-5924

23. Singh, Inderjeet,1978-. Risk-averse periodic preventive maintenance optimization.

Degree: PhD, Operations Research and Industrial Engineering, 2011, University of Texas – Austin

URL: http://hdl.handle.net/2152/ETD-UT-2011-08-4203

► We consider a class of periodic preventive maintenance (PM) optimization problems, for a single piece of equipment that deteriorates with time or use, and can… (more)

▼ We consider a class of periodic preventive maintenance (PM) optimization problems, for a single piece of equipment that deteriorates with time or use, and can be repaired upon failure, through corrective maintenance (CM). We develop analytical and simulation-based optimization models that seek an optimal periodic PM policy, which minimizes the sum of the expected total cost of PMs and the risk-averse cost of CMs, over a finite planning horizon. In the simulation-based models, we assume that both types of maintenance actions are imperfect, whereas our analytical models consider imperfect PMs with minimal CMs. The effectiveness of maintenance actions is modeled using age reduction factors. For a repairable unit of equipment, its virtual age, and not its calendar age, determines the associated failure rate. Therefore, two sets of parameters, one describing the effectiveness of maintenance actions, and the other that defines the underlying failure rate of a piece of equipment, are critical to our models. Under a given maintenance policy, the two sets of parameters and a virtual-age-based age-reduction model, completely define the failure process of a piece of equipment. In practice, the true failure rate, and exact quality of the maintenance actions, cannot be determined, and are often estimated from the equipment failure history. We use a Bayesian approach to parameter estimation, under which a random-walk-based Gibbs sampler provides posterior estimates for the parameters of interest. Our posterior estimates for a few datasets from the literature, are consistent with published results. Furthermore, our computational results successfully demonstrate that our Gibbs sampler is arguably the obvious choice over a general rejection sampling-based parameter estimation method, for this class of problems. We present a general simulation-based periodic PM optimization model, which uses the posterior estimates to simulate the number of operational equipment failures, under a given periodic PM policy. Optimal periodic PM policies, under the classical maximum likelihood (ML) and Bayesian estimates are obtained for a few datasets. Limitations of the ML approach are revealed for a dataset from the literature, in which the use of ML estimates of the parameters, in the maintenance optimization model, fails to capture a trivial optimal PM policy. Finally, we introduce a single-stage and a two-stage formulation of the risk-averse periodic PM optimization model, with imperfect PMs and minimal CMs. Such models apply to a class of complex equipment with many parts, operational failures of which are addressed by replacing or repairing a few parts, thereby not affecting the failure rate of the equipment under consideration. For general values of PM age reduction factors, we provide sufficient conditions to establish the convexity of the first and second moments of the number of failures, and the risk-averse expected total maintenance cost, over a finite planning horizon. For increasing Weibull rates and a general class of increasing… Advisors/Committee Members: Popova, Elmira (advisor), Morton, David P. (advisor), Damien, Paul (committee member), Hasenbein, John J. (committee member), Kutanoglu, Erhan (committee member).

Subjects/Keywords: Risk-averse; Periodic preventive maintenance; Two-stage optimization; Risk-averse cost; Corrective maintenance; Preventive maintenance; Risk-neutral; Bayesian approach; Age reduction factors; Maintenance effectiveness; Virtual age; Kijima-I; Kijima-II; Effective age; Increasing failure rate; Time to first system failures; Likelihood function; Parameter estimation; Simulation-based optimization; Gibbs sampler; Efficient algorithm; As Good As New; As Good As Old; Minimal repair; PM; CM; Risk averse maintenance cost; Computational results; Simulation based preventive maintenance optimization; Nonhomogenous poisson process; Imperfect repair; Imperfect PM; Perfect PM; Finite planning horizon; Nuclear power plant; South Texas Project Nuclear Operating Company; Bayesian methods; Prior; Posterior; ROCOF; Rate of occurrence of failures

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APA (6^th Edition):

Singh, I. (2011). Risk-averse periodic preventive maintenance optimization. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2011-08-4203

Chicago Manual of Style (16^th Edition):

Singh, Inderjeet,1978-. “Risk-averse periodic preventive maintenance optimization.” 2011. Doctoral Dissertation, University of Texas – Austin. Accessed January 24, 2021. http://hdl.handle.net/2152/ETD-UT-2011-08-4203.

MLA Handbook (7^th Edition):

Singh, Inderjeet,1978-. “Risk-averse periodic preventive maintenance optimization.” 2011. Web. 24 Jan 2021.

Vancouver:

Singh I. Risk-averse periodic preventive maintenance optimization. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2011. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/2152/ETD-UT-2011-08-4203.

Council of Science Editors:

Singh I. Risk-averse periodic preventive maintenance optimization. [Doctoral Dissertation]. University of Texas – Austin; 2011. Available from: http://hdl.handle.net/2152/ETD-UT-2011-08-4203

24. Shao, Yufen. Home therapist network modeling.

Degree: PhD, Operations Research and Industrial Engineering, 2011, University of Texas – Austin

URL: http://hdl.handle.net/2152/ETD-UT-2011-12-4500

► Home healthcare has been a growing sector of the economy over the last three decades with roughly 23,000 companies now doing business in the U.S.… (more)

▼ Home healthcare has been a growing sector of the economy over the last three decades with roughly 23,000 companies now doing business in the U.S. producing over $56 billion in combined annual revenue. As a highly fragmented market, profitability of individual companies depends on effective management and efficient operations. This dissertation aims at reducing costs and improving productivity for home healthcare companies. The first part of the research involves the development of a new formulation for the therapist routing and scheduling problem as a mixed integer program. Given the time horizon, a set of therapists and a group of geographically dispersed patients, the objective of the model is to minimize the total cost of providing service by assigning patients to therapists while satisfying a host of constraints concerning time windows, labor regulations and contractual agreements. This problem is NP-hard and proved to be beyond the capability of commercial solvers like CPLEX. To obtain good solutions quickly, three approaches have been developed that include two heuristics and a decomposition algorithm. The first approach is a parallel GRASP that assigns patients to multiple routes in a series of rounds. During the first round, the procedure optimizes the patient distribution among the available therapists, thus trying to reach a local optimum with respect to the combined cost of the routes. Computational results show that the parallel GRASP can reduce costs by 14.54% on average for real datasets, and works efficiently on randomly generated datasets. The second approach is a sequential GRASP that constructs one route at a time. When building a route, the procedure tracks the amount of time used by the therapists each day, giving it tight control over the treatment time distribution within a route. Computational results show that the sequential GRASP provides a cost savings of 18.09% on average for the same real datasets, but gets much better solutions with significantly less CPU for the same randomly generated datasets. The third approach is a branch and price algorithm, which is designed to find exact optima within an acceptable amount of time. By decomposing the full problem by therapist, we obtain a series of constrained shortest path problems, which, by comparison are relatively easy to solve. Computational results show that, this approach is not efficient here because: 1) convergence of Dantzig-Wolfe decomposition is not fast enough; and 2) subproblem is strongly NP-hard and cannot be solved efficiently. The last part of this research studies a simpler case in which all patients have fixed appointment times. The model takes the form of a large-scale mixed-integer program, and has different computational complexity when different features are considered. With the piece-wise linear cost structure, the problem is strongly NP-hard and not solvable with CPLEX for instances of realistic size. Subsequently, a rolling horizon algorithm, two relaxed mixed-integer models and a… Advisors/Committee Members: Bard, Jonathan F. (advisor), Jarrah, Ahmad I. (committee member), Lasdon, Leon (committee member), Morton, David P. (committee member), Kutanoglu, Erhan (committee member).

Subjects/Keywords: Therapist scheduling; Home healthcare; Weekly planning; Network modeling; Mixed integer programming; Exact algorithm; Column generation; Heuristic algorithm; GRASP

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APA (6^th Edition):

Shao, Y. (2011). Home therapist network modeling. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2011-12-4500

Chicago Manual of Style (16^th Edition):

Shao, Yufen. “Home therapist network modeling.” 2011. Doctoral Dissertation, University of Texas – Austin. Accessed January 24, 2021. http://hdl.handle.net/2152/ETD-UT-2011-12-4500.

MLA Handbook (7^th Edition):

Shao, Yufen. “Home therapist network modeling.” 2011. Web. 24 Jan 2021.

Vancouver:

Shao Y. Home therapist network modeling. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2011. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/2152/ETD-UT-2011-12-4500.

Council of Science Editors:

Shao Y. Home therapist network modeling. [Doctoral Dissertation]. University of Texas – Austin; 2011. Available from: http://hdl.handle.net/2152/ETD-UT-2011-12-4500

25. Queiroz, Anderson Rodrigo de. A sampling-based decomposition algorithm with application to hydrothermal scheduling : cut formation and solution quality.

Degree: PhD, Operations Research, 2011, University of Texas – Austin

URL: http://hdl.handle.net/2152/ETD-UT-2011-12-4690

► We consider a hydrothermal scheduling problem with a mid-term horizon(HTSPM) modeled as a large-scale multistage stochastic program with stochastic monthly inflows of water to each… (more)

▼ We consider a hydrothermal scheduling problem with a mid-term horizon(HTSPM) modeled as a large-scale multistage stochastic program with stochastic monthly inflows of water to each hydro generator. In the HTSPM we seek an operating policy to minimize the sum of present and expected future costs, which include thermal generation costs and load curtailment costs. In addition to various simple bounds, problem constraints involve water balance, demand satisfaction and power interchanges. Sampling-based decomposition algorithms (SBDAs) have been used in the literature to solve HTSPM. SBDAs can be used to approximately solve problem instances with many time stages and with inflows that exhibit interstage dependence. Such dependence requires care in computing valid cuts for the decomposition algorithm. In order to help maintain tractability, we employ an aggregate reservoir representation (ARR). In an ARR all the hydro generators inside a specific region are grouped to effectively form one hydro plant with reservoir storage and generation capacity proportional to the parameters of the hydro plants used to form that aggregate reservoir. The ARR has been used in the literature with energy balance constraints, rather than water balance constraints, coupled with time series forecasts of energy inflows. Instead, we prefer as a model primitive to have the time series model forecast water inflows. This, in turn, requires that we extend existing methods to compute valid cuts for the decomposition method under the resulting form of interstage dependence. We form a sample average approximation of the original problem and then solve this problem by these special-purpose algorithms. And, we assess the quality of the resulting policy for operating the system. In our analysis, we compute a confidence interval on the optimality gap of a policy generated by solving an approximation on a sampled scenario tree. We present computational results on test problems with 24 monthly stages in which the inter-stage dependency of hydro inflows is modeled using a dynamic linear model. We further develop a parallel implementation of an SBDA. We apply SBDA to solve the HTSPM for the Brazilian power system that has 150 hydro generators, 151 thermal generators and 4 regions that each characterize an aggregate reservoir. We create and solve four different HTSPM instances where we change the input parameters with respect to generation capacity, transmission capacity and load in order to analyze the difference in the total expected cost. Advisors/Committee Members: Morton, David P. (advisor), Popova, Elmira (committee member), Kutanoglu, Erhan (committee member), Bard, Jonathan F. (committee member), Baldick, Ross (committee member).

Subjects/Keywords: Decomposition algorithms; Stochastic optimization; Multistage mathematical Programs; Hydro-thermal scheduling; Solution quality assessment

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APA (6^th Edition):

Queiroz, A. R. d. (2011). A sampling-based decomposition algorithm with application to hydrothermal scheduling : cut formation and solution quality. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2011-12-4690

Chicago Manual of Style (16^th Edition):

Queiroz, Anderson Rodrigo de. “A sampling-based decomposition algorithm with application to hydrothermal scheduling : cut formation and solution quality.” 2011. Doctoral Dissertation, University of Texas – Austin. Accessed January 24, 2021. http://hdl.handle.net/2152/ETD-UT-2011-12-4690.

MLA Handbook (7^th Edition):

Queiroz, Anderson Rodrigo de. “A sampling-based decomposition algorithm with application to hydrothermal scheduling : cut formation and solution quality.” 2011. Web. 24 Jan 2021.

Vancouver:

Queiroz ARd. A sampling-based decomposition algorithm with application to hydrothermal scheduling : cut formation and solution quality. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2011. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/2152/ETD-UT-2011-12-4690.

Council of Science Editors:

Queiroz ARd. A sampling-based decomposition algorithm with application to hydrothermal scheduling : cut formation and solution quality. [Doctoral Dissertation]. University of Texas – Austin; 2011. Available from: http://hdl.handle.net/2152/ETD-UT-2011-12-4690

26. -1113-1730. Optimization models for manufacturing and personnel scheduling.

Degree: PhD, Operations Research and Industrial Engineering, 2017, University of Texas – Austin

URL: http://hdl.handle.net/2152/61924

► Personnel scheduling problems have been studied by many researchers over the last five decades but much of the literature has ignored the array of break… (more)

▼ Personnel scheduling problems have been studied by many researchers over the last five decades but much of the literature has ignored the array of break types used in practice. We investigate the benefits that flexibility offers in daily shift scheduling, especially when demand is uncertain. The different forms of flexibility considered include shift start times, the number of breaks, break lengths, and break placement. Five related mixed-integer programming models are developed and used to compare break scheduling in advance and either sequentially or in real time for various shift and break profiles. In addition, we investigate the same problem under stochastic demand. We formulate a multi-stage stochastic programming model and then transform it into a two-stage model to ease the computational burden. For testing purpose, we consider 61 scenarios. Five metrics are used for evaluating performance. While the full range of shift and break options are rarely considered in personnel scheduling problems, many practical aspects of machine setups have been neglected in scheduling semiconductor assembly and test (AT) operations. We examine all sides of the problem in a multi-machine, multi-tooling environment to see the impact of using a hierarchical approach to setups on facility performance. The primary objectives of the problem investigated are to minimize the number of shortages of key devices and to maximize weighted throughput, in that order, over a planning horizon of up to five days. Secondary objectives include minimizing the number of machines used to meet output targets, and minimizing makespan. For the shift scheduling problems with flexible breaks the application studied involves airport ground handlers; for the hierarchical machine setup problem for semiconductor assembly and test facilities testing was done with data provided by Texas Instruments. In Chapter 2, we investigate the benefits of flexibility for shifts and breaks with both deterministic and randomized demand. A rolling horizon approach is proposed for real-time break scheduling as demand unfolds over the day. In Chapter 3, we extend the shift scheduling problem to more realistically accommodate stochasticity. We introduce a two-stage stochastic programming model and determine the value of stochastic solutions and the expected value of perfect information. In Chapter 4, we develop an optimization model for scheduling multi-pass lots under hierarchical machine setup rules at assembly and test facilities. We determine machine setups, lot assignments and sequences using a greedy randomized adaptive search procedure. Advisors/Committee Members: Bard, Jonathan F. (advisor), Hasenbein, John J (committee member), Kutanoglu, Erhan (committee member), Kiermaier, Ferdinand (committee member), Frey, Markus (committee member).

Subjects/Keywords: Shift scheduling; Flexible breaks; Rolling horizon framework; Real-time break assignments; Stochastic optimization; Baggage handlers; Implicit modeling of breaks; Semiconductor assembly and test facility; Back-end operations; Hierarchical setups; Reentrant flow; GRASP

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APA (6^th Edition):

-1113-1730. (2017). Optimization models for manufacturing and personnel scheduling. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/61924

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Chicago Manual of Style (16^th Edition):

-1113-1730. “Optimization models for manufacturing and personnel scheduling.” 2017. Doctoral Dissertation, University of Texas – Austin. Accessed January 24, 2021. http://hdl.handle.net/2152/61924.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

MLA Handbook (7^th Edition):

-1113-1730. “Optimization models for manufacturing and personnel scheduling.” 2017. Web. 24 Jan 2021.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

-1113-1730. Optimization models for manufacturing and personnel scheduling. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2017. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/2152/61924.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

-1113-1730. Optimization models for manufacturing and personnel scheduling. [Doctoral Dissertation]. University of Texas – Austin; 2017. Available from: http://hdl.handle.net/2152/61924

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

27. Bregenzer, Brent Constant. Control-friendly scheduling algorithms for multi-tool, multi-product manufacturing systems.

Degree: PhD, Chemical Engineering, 2011, University of Texas – Austin

URL: http://hdl.handle.net/2152/ETD-UT-2011-12-4416

► The fabrication of semiconductor devices is a highly competitive and capital intensive industry. Due to the high costs of building wafer fabrication facilities (fabs), it… (more)

▼ The fabrication of semiconductor devices is a highly competitive and capital intensive industry. Due to the high costs of building wafer fabrication facilities (fabs), it is expected that products should be made efficiently with respect to both time and material, and that expensive unit operations (tools) should be utilized as much as possible. The process flow is characterized by frequent machine failures, drifting tool states, parallel processing, and reentrant flows. In addition, the competitive nature of the industry requires products to be made quickly and within tight tolerances. All of these factors conspire to make both the scheduling of product flow through the system and the control of product quality metrics extremely difficult. Up to now, much research has been done on the two problems separately, but until recently, interactions between the two systems, which can sometimes be detrimental to one another, have mostly been ignored. The research contained here seeks to tackle the scheduling problem by utilizing objectives based on control system parameters in order that the two systems might behave in a more beneficial manner. A non-threaded control system is used that models the multi-tool, multi-product process in a state space form, and estimates the states using a Kalman filter. Additionally, the process flow is modeled by a discrete event simulation. The two systems are then merged to give a representation of the overall system. Two control system matrices, the estimate error covariance matrix from the Kalman filter and a square form of the system observability matrix called the information matrix, are used to generate several control-based scheduling algorithms. These methods are then tested against more tradition approaches from the scheduling literature to determine their effectiveness on both the basis of how well they maintain the outputs near their targets and how well they minimize the cycle time of the products in the system. The two metrics are viewed simultaneously through use of Pareto plots and merits of the various scheduling methods are judged on the basis of Pareto optimality for several test cases. Advisors/Committee Members: Qin, Joe (advisor), Hasenbein, John J. (advisor), Edgar, Thomas F. (advisor), Hwang, Gyeong S. (committee member), Kutanoglu, Erhan (committee member), Bonnecaze, Roger T. (committee member).

Subjects/Keywords: Semiconductor; Process control; Run-to-run; Scheduling; Dispatching; Kalman filter; Interaction; Pareto

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APA (6^th Edition):

Bregenzer, B. C. (2011). Control-friendly scheduling algorithms for multi-tool, multi-product manufacturing systems. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2011-12-4416

Chicago Manual of Style (16^th Edition):

Bregenzer, Brent Constant. “Control-friendly scheduling algorithms for multi-tool, multi-product manufacturing systems.” 2011. Doctoral Dissertation, University of Texas – Austin. Accessed January 24, 2021. http://hdl.handle.net/2152/ETD-UT-2011-12-4416.

MLA Handbook (7^th Edition):

Bregenzer, Brent Constant. “Control-friendly scheduling algorithms for multi-tool, multi-product manufacturing systems.” 2011. Web. 24 Jan 2021.

Vancouver:

Bregenzer BC. Control-friendly scheduling algorithms for multi-tool, multi-product manufacturing systems. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2011. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/2152/ETD-UT-2011-12-4416.

Council of Science Editors:

Bregenzer BC. Control-friendly scheduling algorithms for multi-tool, multi-product manufacturing systems. [Doctoral Dissertation]. University of Texas – Austin; 2011. Available from: http://hdl.handle.net/2152/ETD-UT-2011-12-4416

28. Qu, Yuan, Ph. D. Pickup and delivery problems with side constraints.

Degree: PhD, Operations Research and Industrial Engineering, 2012, University of Texas – Austin

URL: http://hdl.handle.net/2152/19531

► Pickup and delivery problems (PDPs) have been studied extensively in past decades. A wide variety of research exits on both exact algorithms and heuristics for… (more)

▼ Pickup and delivery problems (PDPs) have been studied extensively in past decades. A wide variety of research exits on both exact algorithms and heuristics for generic variations of the problem as well as real-life applications, which continue to spark new challenges and open up new opportunities for researchers. In this dissertation, we study two variations of pickup and delivery problem that arise in industry and develop new computational methods that are shown to be effective with respect to existing algorithms and scheduling procedures found in practice. The first problem is the pickup and delivery problem with transshipment (PDPT). The work presented here was inspired by a daily route planning problem at a regional air carrier. In structuring the analysis, we describe a unique way to model the transshipment option on a directed graph. With the graph as the foundation, we implemented a branch and price algorithm. Preliminary results showed that it has difficulty in solving large instances. As an alternative, we developed a greedy randomized adaptive search procedure (GRASP) with several novel features. In the construction phase, shipment requests are inserted into routes until all demand is satisfied or no feasible insertion exists. In the improvement phase, an adaptive large neighborhood search algorithm is used to reconstruct portions of the feasible routes. Specialized removal and insertion heuristics were designed for this purpose. We also developed a procedure for generating problem instances in the absence of any in the literature. Testing was done on existing PDP data sets and generated PDPT data set. For the former, the performance and solution quality of the GRASP were comparable to the best known heuristics. For the latter, GRASP found the near optimal solution in most test cases. In the second part of the dissertation, we focus on a new version of the heterogeneous PDP in which the capacity of each vehicle can be modified by reconfiguring its interior to satisfy different types of customer demands. The work was motivated by a daily route planning problem arising at a senior activity center. A fleet of configurable vans is available each day to transport participants to and from the center as well as to secondary facilities for rehabilitative and medical treatment. To find solutions, we developed a two-phase heuristic that makes use of ideas from greedy randomized adaptive search procedures with multiple starts. In phase I, a set of good feasible solutions is constructed using a series of randomized procedures. A representative subset of those solutions is selected as candidates for improvement by solving a max diversity problem. In phase II, an adaptive large neighborhood search (ALNS) heuristic is used to find local optima by reconstructing portions of the feasible routes. Also, a specialized route feasibility check with vehicle type reassignment is introduced to take full advantage of the heterogeneous nature of vehicles. The effectiveness of the proposed methodology is demonstrated by… Advisors/Committee Members: Bard, Jonathan F. (advisor), Lasdon, Leon (committee member), Morton, David P (committee member), Kutanoglu, Erhan (committee member), Pachon, Julian (committee member).

Subjects/Keywords: Pickup and delivery; Transshipment; GRASP; ALNS; Branch and price; Column generation; Configurable vehicle capacity; MSALNS; Branch and price and cut

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APA (6^th Edition):

Qu, Yuan, P. D. (2012). Pickup and delivery problems with side constraints. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/19531

Chicago Manual of Style (16^th Edition):

Qu, Yuan, Ph D. “Pickup and delivery problems with side constraints.” 2012. Doctoral Dissertation, University of Texas – Austin. Accessed January 24, 2021. http://hdl.handle.net/2152/19531.

MLA Handbook (7^th Edition):

Qu, Yuan, Ph D. “Pickup and delivery problems with side constraints.” 2012. Web. 24 Jan 2021.

Vancouver:

Qu, Yuan PD. Pickup and delivery problems with side constraints. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2012. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/2152/19531.

Council of Science Editors:

Qu, Yuan PD. Pickup and delivery problems with side constraints. [Doctoral Dissertation]. University of Texas – Austin; 2012. Available from: http://hdl.handle.net/2152/19531

29. Derinkuyu, Kursad. Optimization models for transport and service scheduling.

Degree: PhD, Operations Research and Industrial Engineering, 2011, University of Texas – Austin

URL: http://hdl.handle.net/2152/ETD-UT-2011-05-3422

► This dissertation focuses on service scheduling and transshipment problems. The study of service scheduling is motivated by decisions facing service planners, who must inspect and… (more)

▼ This dissertation focuses on service scheduling and transshipment problems. The study of service scheduling is motivated by decisions facing service planners, who must inspect and maintain geographically dispersed infrastructure facilities. We study the problem of deciding which operations a service unit must perform at each customer location, given the sequence in which the unit periodically visits these locations. Each customer requires multiple service operations, and each operation has a time-varying completion or penalty cost that depends on the previous service time. The goal is to schedule the service start time for each customer and select the operations to perform so as to minimize the total completion cost. We first discuss how to solve a special case of this problem in which each site is visited only once per service cycle. We formulate this problem as a discrete time indexed network flow problem and prove that it is NP-hard in the ordinary sense. Then, we represent the problem as a multidimensional shortest path problem with path-dependent arc lengths. In this structure, arc costs depend on the total time spent for all customers. The resulting formulation is solvable via algorithms that have pseudo-polynomial run times. Computational results show that the shortest path approach outperformed the general network flow model. We then analyze the general case of this problem, in which each site can be visited more than once and prove that the problem is NP-Hard in the strong sense. We discuss the valid cuts and describe the preprocessor that reduces the problem size. Next, we examine an application to the general case of the problem and develop a fast and effective heuristic procedure that repeatedly applies the shortest path approach to subsequences that do not visit any customer more than once. Computational results for several problem instances show that the proposed heuristic identifies near optimal results very quickly, whereas a general purpose integer-programming solver (CPLEX) is not able to find an optimal solution even after many hours of computational time. Then we focus on techniques such as problem reduction, branching variables, and subdividing problem to smaller problems to get better solution times for the actual problem. Computational results show that these techniques can improve solution times substantially. Finally, we study a transshipment problem, in which the shipments need to be transported from their origin to destination and are subject to the logical and physical transportation network on which they rely. We consider a space-time network that allows one to formulate the problem as a multi-commodity network flow problem with additional side constraints and show the complexity results. We propose alternative models and propose algorithms for lower and upper bound calculations. Advisors/Committee Members: Balakrishnan, Anant (advisor), Kutanoglu, Erhan (advisor), Bard, Jonathan F. (committee member), Morton, David P. (committee member), Waller, Travis S. (committee member).

Subjects/Keywords: Service scheduling; Maintenance; Transportation; Time-space network

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Derinkuyu, K. (2011). Optimization models for transport and service scheduling. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2011-05-3422

Chicago Manual of Style (16^th Edition):

Derinkuyu, Kursad. “Optimization models for transport and service scheduling.” 2011. Doctoral Dissertation, University of Texas – Austin. Accessed January 24, 2021. http://hdl.handle.net/2152/ETD-UT-2011-05-3422.

MLA Handbook (7^th Edition):

Derinkuyu, Kursad. “Optimization models for transport and service scheduling.” 2011. Web. 24 Jan 2021.

Vancouver:

Derinkuyu K. Optimization models for transport and service scheduling. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2011. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/2152/ETD-UT-2011-05-3422.

Council of Science Editors:

Derinkuyu K. Optimization models for transport and service scheduling. [Doctoral Dissertation]. University of Texas – Austin; 2011. Available from: http://hdl.handle.net/2152/ETD-UT-2011-05-3422

University of Texas – Austin

30. Chandrasekhar, Rohan. Fixed-income portfolio optimization.

Degree: MSin Engineering, Operations Research and Industrial Engineering, 2009, University of Texas – Austin

URL: http://hdl.handle.net/2152/ETD-UT-2009-12-631

► The fixed maturity, pricing and cash flow characteristics of fixed-income instruments like bonds distinguish them from equities and complicate the application of mean-variance optimization techniques… (more)

Subjects/Keywords: Bonds; Bond portfolios

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Chandrasekhar, R. (2009). Fixed-income portfolio optimization. (Masters Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2009-12-631

Chicago Manual of Style (16^th Edition):

Chandrasekhar, Rohan. “Fixed-income portfolio optimization.” 2009. Masters Thesis, University of Texas – Austin. Accessed January 24, 2021. http://hdl.handle.net/2152/ETD-UT-2009-12-631.

MLA Handbook (7^th Edition):

Chandrasekhar, Rohan. “Fixed-income portfolio optimization.” 2009. Web. 24 Jan 2021.

Vancouver:

Chandrasekhar R. Fixed-income portfolio optimization. [Internet] [Masters thesis]. University of Texas – Austin; 2009. [cited 2021 Jan 24]. Available from: http://hdl.handle.net/2152/ETD-UT-2009-12-631.

Council of Science Editors:

Chandrasekhar R. Fixed-income portfolio optimization. [Masters Thesis]. University of Texas – Austin; 2009. Available from: http://hdl.handle.net/2152/ETD-UT-2009-12-631

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