Advanced search options

Advanced Search Options 🞨

Browse by author name (“Author name starts with…”).

Find ETDs with:

in
/  
in
/  
in
/  
in

Written in Published in Earliest date Latest date

Sorted by

Results per page:

Sorted by: relevance · author · university · dateNew search

You searched for +publisher:"University of Arizona" +contributor:("Bayraksan, Guzin"). Showing records 1 – 7 of 7 total matches.

Search Limiters

Last 2 Years | English Only

No search limiters apply to these results.

▼ Search Limiters


University of Arizona

1. Love, David Keith. Data-Driven Methods for Optimization Under Uncertainty with Application to Water Allocation .

Degree: 2013, University of Arizona

 Stochastic programming is a mathematical technique for decision making under uncertainty using probabilistic statements in the problem objective and constraints. In practice, the distribution of… (more)

Subjects/Keywords: overlapping batches; phi divergence; Stochastic programming; water allocation; Applied Mathematics; Distributionally robust optimization

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Love, D. K. (2013). Data-Driven Methods for Optimization Under Uncertainty with Application to Water Allocation . (Doctoral Dissertation). University of Arizona. Retrieved from http://hdl.handle.net/10150/311177

Chicago Manual of Style (16th Edition):

Love, David Keith. “Data-Driven Methods for Optimization Under Uncertainty with Application to Water Allocation .” 2013. Doctoral Dissertation, University of Arizona. Accessed December 07, 2019. http://hdl.handle.net/10150/311177.

MLA Handbook (7th Edition):

Love, David Keith. “Data-Driven Methods for Optimization Under Uncertainty with Application to Water Allocation .” 2013. Web. 07 Dec 2019.

Vancouver:

Love DK. Data-Driven Methods for Optimization Under Uncertainty with Application to Water Allocation . [Internet] [Doctoral dissertation]. University of Arizona; 2013. [cited 2019 Dec 07]. Available from: http://hdl.handle.net/10150/311177.

Council of Science Editors:

Love DK. Data-Driven Methods for Optimization Under Uncertainty with Application to Water Allocation . [Doctoral Dissertation]. University of Arizona; 2013. Available from: http://hdl.handle.net/10150/311177


University of Arizona

2. Zhang, Weini. Water Network Design and Management via Stochastic Programming .

Degree: 2013, University of Arizona

 Water is an essential natural resource for life and economic activities. Water resources management is facing major challenges due to increasing demands caused by population… (more)

Subjects/Keywords: Systems & Industrial Engineering

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Zhang, W. (2013). Water Network Design and Management via Stochastic Programming . (Doctoral Dissertation). University of Arizona. Retrieved from http://hdl.handle.net/10150/311556

Chicago Manual of Style (16th Edition):

Zhang, Weini. “Water Network Design and Management via Stochastic Programming .” 2013. Doctoral Dissertation, University of Arizona. Accessed December 07, 2019. http://hdl.handle.net/10150/311556.

MLA Handbook (7th Edition):

Zhang, Weini. “Water Network Design and Management via Stochastic Programming .” 2013. Web. 07 Dec 2019.

Vancouver:

Zhang W. Water Network Design and Management via Stochastic Programming . [Internet] [Doctoral dissertation]. University of Arizona; 2013. [cited 2019 Dec 07]. Available from: http://hdl.handle.net/10150/311556.

Council of Science Editors:

Zhang W. Water Network Design and Management via Stochastic Programming . [Doctoral Dissertation]. University of Arizona; 2013. Available from: http://hdl.handle.net/10150/311556


University of Arizona

3. Zhou, Zhihong. Multistage Stochastic Decomposition and its Applications .

Degree: 2012, University of Arizona

 In this dissertation, we focus on developing sampling-based algorithms for solving stochastic linear programs. The work covers both two stage and multistage versions of stochastic… (more)

Subjects/Keywords: Optimization Simulation; Stage-wise Independence; Stochastic Decomposition; Stochastic Dual Dynamic Programming; Systems & Industrial Engineering; Multistage Stochastic Decomposition; Multistage Stochastic Program

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Zhou, Z. (2012). Multistage Stochastic Decomposition and its Applications . (Doctoral Dissertation). University of Arizona. Retrieved from http://hdl.handle.net/10150/222892

Chicago Manual of Style (16th Edition):

Zhou, Zhihong. “Multistage Stochastic Decomposition and its Applications .” 2012. Doctoral Dissertation, University of Arizona. Accessed December 07, 2019. http://hdl.handle.net/10150/222892.

MLA Handbook (7th Edition):

Zhou, Zhihong. “Multistage Stochastic Decomposition and its Applications .” 2012. Web. 07 Dec 2019.

Vancouver:

Zhou Z. Multistage Stochastic Decomposition and its Applications . [Internet] [Doctoral dissertation]. University of Arizona; 2012. [cited 2019 Dec 07]. Available from: http://hdl.handle.net/10150/222892.

Council of Science Editors:

Zhou Z. Multistage Stochastic Decomposition and its Applications . [Doctoral Dissertation]. University of Arizona; 2012. Available from: http://hdl.handle.net/10150/222892


University of Arizona

4. Basudhar, Anirban. Computational Optimal Design and Uncertainty Quantification of Complex Systems Using Explicit Decision Boundaries .

Degree: 2011, University of Arizona

 This dissertation presents a sampling-based method that can be used for uncertainty quantification and deterministic or probabilistic optimization. The objective is to simultaneously address several… (more)

Subjects/Keywords: explicit decision boundaries; multiple failure modes; reliability based design optimization; support vector machines; Mechanical Engineering; adaptive sampling; discontinuous and binary responses

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Basudhar, A. (2011). Computational Optimal Design and Uncertainty Quantification of Complex Systems Using Explicit Decision Boundaries . (Doctoral Dissertation). University of Arizona. Retrieved from http://hdl.handle.net/10150/201491

Chicago Manual of Style (16th Edition):

Basudhar, Anirban. “Computational Optimal Design and Uncertainty Quantification of Complex Systems Using Explicit Decision Boundaries .” 2011. Doctoral Dissertation, University of Arizona. Accessed December 07, 2019. http://hdl.handle.net/10150/201491.

MLA Handbook (7th Edition):

Basudhar, Anirban. “Computational Optimal Design and Uncertainty Quantification of Complex Systems Using Explicit Decision Boundaries .” 2011. Web. 07 Dec 2019.

Vancouver:

Basudhar A. Computational Optimal Design and Uncertainty Quantification of Complex Systems Using Explicit Decision Boundaries . [Internet] [Doctoral dissertation]. University of Arizona; 2011. [cited 2019 Dec 07]. Available from: http://hdl.handle.net/10150/201491.

Council of Science Editors:

Basudhar A. Computational Optimal Design and Uncertainty Quantification of Complex Systems Using Explicit Decision Boundaries . [Doctoral Dissertation]. University of Arizona; 2011. Available from: http://hdl.handle.net/10150/201491


University of Arizona

5. Celik, Nurcin. INTEGRATED DECISION MAKING FOR PLANNING AND CONTROL OF DISTRIBUTED MANUFACTURING ENTERPRISES USING DYNAMIC-DATA-DRIVEN ADAPTIVE MULTI-SCALE SIMULATIONS (DDDAMS) .

Degree: 2010, University of Arizona

 Discrete-event simulation has become one of the most widely used analysis tools for large-scale, complex and dynamic systems such as supply chains as it can… (more)

Subjects/Keywords: Adaptive simulations; Distributed simulation; Dynamic data driven simulations; Particle filtering; Resampling rules; Simulation-based control

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Celik, N. (2010). INTEGRATED DECISION MAKING FOR PLANNING AND CONTROL OF DISTRIBUTED MANUFACTURING ENTERPRISES USING DYNAMIC-DATA-DRIVEN ADAPTIVE MULTI-SCALE SIMULATIONS (DDDAMS) . (Doctoral Dissertation). University of Arizona. Retrieved from http://hdl.handle.net/10150/195427

Chicago Manual of Style (16th Edition):

Celik, Nurcin. “INTEGRATED DECISION MAKING FOR PLANNING AND CONTROL OF DISTRIBUTED MANUFACTURING ENTERPRISES USING DYNAMIC-DATA-DRIVEN ADAPTIVE MULTI-SCALE SIMULATIONS (DDDAMS) .” 2010. Doctoral Dissertation, University of Arizona. Accessed December 07, 2019. http://hdl.handle.net/10150/195427.

MLA Handbook (7th Edition):

Celik, Nurcin. “INTEGRATED DECISION MAKING FOR PLANNING AND CONTROL OF DISTRIBUTED MANUFACTURING ENTERPRISES USING DYNAMIC-DATA-DRIVEN ADAPTIVE MULTI-SCALE SIMULATIONS (DDDAMS) .” 2010. Web. 07 Dec 2019.

Vancouver:

Celik N. INTEGRATED DECISION MAKING FOR PLANNING AND CONTROL OF DISTRIBUTED MANUFACTURING ENTERPRISES USING DYNAMIC-DATA-DRIVEN ADAPTIVE MULTI-SCALE SIMULATIONS (DDDAMS) . [Internet] [Doctoral dissertation]. University of Arizona; 2010. [cited 2019 Dec 07]. Available from: http://hdl.handle.net/10150/195427.

Council of Science Editors:

Celik N. INTEGRATED DECISION MAKING FOR PLANNING AND CONTROL OF DISTRIBUTED MANUFACTURING ENTERPRISES USING DYNAMIC-DATA-DRIVEN ADAPTIVE MULTI-SCALE SIMULATIONS (DDDAMS) . [Doctoral Dissertation]. University of Arizona; 2010. Available from: http://hdl.handle.net/10150/195427


University of Arizona

6. Keller, Brian. Models and Methods for Multiple Resource Constrained Job Scheduling under Uncertainty .

Degree: 2009, University of Arizona

 We consider a scheduling problem where each job requires multiple classes of resources, which we refer to as the multiple resource constrained scheduling problem(MRCSP). Potential… (more)

Subjects/Keywords: disjunctive decomposition; sampling; stochastic integer programming; stochastic scheduling

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Keller, B. (2009). Models and Methods for Multiple Resource Constrained Job Scheduling under Uncertainty . (Doctoral Dissertation). University of Arizona. Retrieved from http://hdl.handle.net/10150/193630

Chicago Manual of Style (16th Edition):

Keller, Brian. “Models and Methods for Multiple Resource Constrained Job Scheduling under Uncertainty .” 2009. Doctoral Dissertation, University of Arizona. Accessed December 07, 2019. http://hdl.handle.net/10150/193630.

MLA Handbook (7th Edition):

Keller, Brian. “Models and Methods for Multiple Resource Constrained Job Scheduling under Uncertainty .” 2009. Web. 07 Dec 2019.

Vancouver:

Keller B. Models and Methods for Multiple Resource Constrained Job Scheduling under Uncertainty . [Internet] [Doctoral dissertation]. University of Arizona; 2009. [cited 2019 Dec 07]. Available from: http://hdl.handle.net/10150/193630.

Council of Science Editors:

Keller B. Models and Methods for Multiple Resource Constrained Job Scheduling under Uncertainty . [Doctoral Dissertation]. University of Arizona; 2009. Available from: http://hdl.handle.net/10150/193630


University of Arizona

7. Reich, Daniel. Stochastic Networks: Tractable Approaches for Identifying Strategic Paths .

Degree: 2009, University of Arizona

 In Chapter 1, we present a stochastic shortest path problem that we refer to as the Most Likely Path Problem (MLPP). We prove that optimal… (more)

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Reich, D. (2009). Stochastic Networks: Tractable Approaches for Identifying Strategic Paths . (Doctoral Dissertation). University of Arizona. Retrieved from http://hdl.handle.net/10150/194439

Chicago Manual of Style (16th Edition):

Reich, Daniel. “Stochastic Networks: Tractable Approaches for Identifying Strategic Paths .” 2009. Doctoral Dissertation, University of Arizona. Accessed December 07, 2019. http://hdl.handle.net/10150/194439.

MLA Handbook (7th Edition):

Reich, Daniel. “Stochastic Networks: Tractable Approaches for Identifying Strategic Paths .” 2009. Web. 07 Dec 2019.

Vancouver:

Reich D. Stochastic Networks: Tractable Approaches for Identifying Strategic Paths . [Internet] [Doctoral dissertation]. University of Arizona; 2009. [cited 2019 Dec 07]. Available from: http://hdl.handle.net/10150/194439.

Council of Science Editors:

Reich D. Stochastic Networks: Tractable Approaches for Identifying Strategic Paths . [Doctoral Dissertation]. University of Arizona; 2009. Available from: http://hdl.handle.net/10150/194439

.