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You searched for subject:(Coordination heuristic). Showing records 1 – 3 of 3 total matches.

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Rochester Institute of Technology

1. Rungta, Viabhav. System Level Impacts of V2X Enabled Vehicle Control Strategies.

Degree: MS, Industrial and Systems Engineering, 2018, Rochester Institute of Technology

With an increasing number of vehicles on road the quantity of CO2 emissions and the amount of fuel wasted because of traffic congestion have been rising. Use of alternate means of transport that generate fewer emissions does not resolve the problem of congestions and vehicle wait time at traffic signal whereas further expansion of existing network of roads is not only constrained by finite space, but any network can get saturated as the number of vehicles increase. V2X technology allows vehicles and traffic infrastructure to communicate with each other, and could facilitate better use of existing resources by providing vehicles information about their surroundings and traffic signals. The information regarding the phase of traffic signal, vehicles’ position and vehicles’ speed can be used by drivers and autonomous vehicle control algorithms to make informed decisions as they approach traffic signals. This research proposes and analyzes system level impacts of implementing a coordination heuristic over single-vehicle optimization to realize the true potential of V2X technology. The results of this research can help policymakers choose the most suitable control strategy depending on the traffic conditions and the penetration rate of V2X technology. The analysis indicates that at 900 vehicles per hour for either of the two driving strategies: coordination heuristic or single-vehicle optimization, to be more preferred over baseline driver behavior, at least 50% of the vehicles should be V2X capable. Once a threshold penetration rate of V2X vehicles is achieved, vehicles following coordination heuristic generate nearly 10% fewer CO2 emissions than vehicles following baseline driver behavior, a 30% improvement over the reduction in CO2 emissions obtained using single-vehicle optimization. The vehicles following the coordination heuristic also have less travel time than vehicles following single-vehicle optimization, and less wait times than vehicles following baseline driver behavior. Advisors/Committee Members: Katie McConky, Michael E. Kuhl.

Subjects/Keywords: Coordination heuristic; Non-linear constraints; Reducing CO2 emission; System level impact; Traffic simulation; V2X technology

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APA (6th Edition):

Rungta, V. (2018). System Level Impacts of V2X Enabled Vehicle Control Strategies. (Masters Thesis). Rochester Institute of Technology. Retrieved from https://scholarworks.rit.edu/theses/9720

Chicago Manual of Style (16th Edition):

Rungta, Viabhav. “System Level Impacts of V2X Enabled Vehicle Control Strategies.” 2018. Masters Thesis, Rochester Institute of Technology. Accessed March 21, 2019. https://scholarworks.rit.edu/theses/9720.

MLA Handbook (7th Edition):

Rungta, Viabhav. “System Level Impacts of V2X Enabled Vehicle Control Strategies.” 2018. Web. 21 Mar 2019.

Vancouver:

Rungta V. System Level Impacts of V2X Enabled Vehicle Control Strategies. [Internet] [Masters thesis]. Rochester Institute of Technology; 2018. [cited 2019 Mar 21]. Available from: https://scholarworks.rit.edu/theses/9720.

Council of Science Editors:

Rungta V. System Level Impacts of V2X Enabled Vehicle Control Strategies. [Masters Thesis]. Rochester Institute of Technology; 2018. Available from: https://scholarworks.rit.edu/theses/9720


The Ohio State University

2. Liu, Zhixin. Capacity allocation and rescheduling in supply chains.

Degree: PhD, Business Administration, 2007, The Ohio State University

First, we study the problem of rescheduling for multiple new orders. Assume that a set of original jobs has been scheduled on a single machine, but not processed, when a set of new jobs arrives. The decision maker needs to insert the new jobs into the existing schedule without excessively changing it. The objective is minimization of the maximum lateness of the jobs, subject to a customer service requirement modeled by a limit on the maximum time change of the original jobs. We show that this scheduling problem is intractable, even if no new jobs arrive. We describe several approximation algorithms and analyze their worst-case performance. Next, we develop a branch and bound algorithm that solves 99.9% of randomly generated instances with up to 1000 jobs within 60 seconds. Second, we consider a multiple product supply chain where a manufacturer receives orders from several distributors. If the orders cannot all be met from available production capacity, then the manufacturer allocates that capacity among the distributors. The distributors may share their allocated capacity among themselves before submitting revised orders. Finally, the manufacturer schedules the revised orders to minimize its cost. We consider three practical coordination issues. First, we estimate the benefit to the manufacturer from considering scheduling costs and constraints in making capacity allocation decisions. Second, we estimate the additional profit that the distributors achieve when they share their allocated capacity. Third, we estimate the value of coordination between the manufacturer and the distributors. Third, we consider a problem where a group of agents, each with a set of jobs, need to schedule their jobs on a common processing facility. Each agent wants to minimize an objective function which depends on its own job completion times. Time slots are allocated to the various jobs based on the bids of the participating agents. We investigate the efficiency and effectiveness of three ascending auction mechanisms, with market goods consisting of time slots, fixed time blocks, and flexible time blocks, respectively. We show that for the case of time blocks, there may not exist an equilibrium solution that is globally optimal. Advisors/Committee Members: Hall, Nicholas (Advisor).

Subjects/Keywords: Business Administration, Management; deterministic scheduling; rescheduling for new job disruptions; heuristic worstcase analysis; branch and bound algorithm; supply chain; capacity allocation; cooperative game; value of coordination; noncooperative game; auction mechanism

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

APA (6th Edition):

Liu, Z. (2007). Capacity allocation and rescheduling in supply chains. (Doctoral Dissertation). The Ohio State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=osu1187883767

Chicago Manual of Style (16th Edition):

Liu, Zhixin. “Capacity allocation and rescheduling in supply chains.” 2007. Doctoral Dissertation, The Ohio State University. Accessed March 21, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1187883767.

MLA Handbook (7th Edition):

Liu, Zhixin. “Capacity allocation and rescheduling in supply chains.” 2007. Web. 21 Mar 2019.

Vancouver:

Liu Z. Capacity allocation and rescheduling in supply chains. [Internet] [Doctoral dissertation]. The Ohio State University; 2007. [cited 2019 Mar 21]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1187883767.

Council of Science Editors:

Liu Z. Capacity allocation and rescheduling in supply chains. [Doctoral Dissertation]. The Ohio State University; 2007. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1187883767

3. Fu, Liangliang. Coordination d'ordonnancement de production et de distribution : Coordination of production and distribution scheduling.

Degree: Docteur es, Informatique, 2014, Paris 9

Dans cette thèse, nous étudions trois problèmes d'ordonnancement de la chaîne logistique dans le modèle de production à la demande. Le premier problème est un problème d'ordonnancement de production et de distribution intermédiaire dans une chaîne logistique avec un producteur et un prestataire logistique. Le deuxième problème est un problème d'ordonnancement de production et de distribution aval avec des dates de début au plus tôt et des dates limites de livraison dans une chaîne logistique avec un producteur, un prestataire logistique et un client. Le troisième problème est un problème d'ordonnancement de production et de distribution aval avec des temps de réglage et des fenêtres de temps de livraison dans une chaîne logistique avec un producteur, un prestataire logistique et plusieurs clients. Pour les trois problèmes, nous étudions les problèmes d'ordonnancement individuels et les problèmes d'ordonnancement coordonnés. Nous proposons des algorithmes polynomiaux ou prouvons la NP-Complétude de ces problèmes, et développons des algorithmes exacts ou heuristiques pour résoudre les problèmes NP-Difficiles. Nous proposons des mécanismes de coordination et évaluons le bénéfice de la coordination.

In this dissertation, we aim at investigating three supply chain scheduling problems in the make-To-Order business model. The first problem is a production and interstage distribution scheduling problem in a supply chain with a manufacturer and a third-Party logistics (3PL) provider. The second problem is a production and outbound distribution scheduling problem with release dates and deadlines in a supply chain with a manufacturer, a 3PL provider and a customer. The third problem is a production and outbound distribution scheduling problem with setup times and delivery time windows in a supply chain with a manufacturer, a 3PL provider and several customers. For the three problems, we study their individual scheduling problems and coordinated scheduling problems: we propose polynomial-Time algorithms or prove the intractability of these problems, and develop exact algorithms or heuristics to solve the NP-Hard problems. We establish mechanisms of coordination and evaluate the benefits of coordination.

Advisors/Committee Members: Aloulou, Mohamed Ali (thesis director).

Subjects/Keywords: Ordonnancement de la chaîne logistique; Coordination; Ordonnancement de production et de distribution; Programmation dynamique; Algorithme par séparation et évaluation; Heuristique; Supply chain scheduling; Coordination; Production and distribution scheduling; Dynamic programming; Branch-And-Bound algorithm; Heuristic; 003

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

APA (6th Edition):

Fu, L. (2014). Coordination d'ordonnancement de production et de distribution : Coordination of production and distribution scheduling. (Doctoral Dissertation). Paris 9. Retrieved from http://www.theses.fr/2014PA090046

Chicago Manual of Style (16th Edition):

Fu, Liangliang. “Coordination d'ordonnancement de production et de distribution : Coordination of production and distribution scheduling.” 2014. Doctoral Dissertation, Paris 9. Accessed March 21, 2019. http://www.theses.fr/2014PA090046.

MLA Handbook (7th Edition):

Fu, Liangliang. “Coordination d'ordonnancement de production et de distribution : Coordination of production and distribution scheduling.” 2014. Web. 21 Mar 2019.

Vancouver:

Fu L. Coordination d'ordonnancement de production et de distribution : Coordination of production and distribution scheduling. [Internet] [Doctoral dissertation]. Paris 9; 2014. [cited 2019 Mar 21]. Available from: http://www.theses.fr/2014PA090046.

Council of Science Editors:

Fu L. Coordination d'ordonnancement de production et de distribution : Coordination of production and distribution scheduling. [Doctoral Dissertation]. Paris 9; 2014. Available from: http://www.theses.fr/2014PA090046

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