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A decomposition and selection method...

Huang, Yong.

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A decomposition and selection method for solving VRPSTW and DEA applications.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	A decomposition and selection method for solving VRPSTW and DEA applications./
作者:	Huang, Yong.
面頁冊數:	153 p.
附註:	Adviser: Ervin Y. Rodin.
Contained By:	Dissertation Abstracts International67-02B.
標題:	Operations Research. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3207216
ISBN:	9780542557866

A decomposition and selection method for solving VRPSTW and DEA applications.
Huang, Yong.

A decomposition and selection method for solving VRPSTW and DEA applications. - 153 p.

Adviser: Ervin Y. Rodin.

Thesis (D.Sc.)--Washington University in St. Louis, 2005.

The Vehicle Routing Problem with Time Windows (VRPTW) examines certain types of scheduling problems, in which the schedule of the fleet is to be determined, such that all customers are serviced within the customers' time windows, and the operational cost for the fleet is minimized. When considering soft time windows, late services are allowed, but the late times are subject to penalties. For large VRPTW, finding a solution is very hard computationally. Therefore, recent researchers are mainly focused on designing heuristics, which find good and feasible solutions in limited time.

ISBN: 9780542557866Subjects--Topical Terms:

626629
Operations Research.

A decomposition and selection method for solving VRPSTW and DEA applications.
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245 1 2 $a A decomposition and selection method for solving VRPSTW and DEA applications.
300 $a 153 p.
500 $a Adviser: Ervin Y. Rodin.
500 $a Source: Dissertation Abstracts International, Volume: 67-02, Section: B, page: 1133.
502 $a Thesis (D.Sc.)--Washington University in St. Louis, 2005.
520 $a The Vehicle Routing Problem with Time Windows (VRPTW) examines certain types of scheduling problems, in which the schedule of the fleet is to be determined, such that all customers are serviced within the customers' time windows, and the operational cost for the fleet is minimized. When considering soft time windows, late services are allowed, but the late times are subject to penalties. For large VRPTW, finding a solution is very hard computationally. Therefore, recent researchers are mainly focused on designing heuristics, which find good and feasible solutions in limited time.
520 $a We present a new heuristic called the Decomposition and Selection Method in this dissertation. It solves certain medium sized VRP with Soft Time Windows. First, we decompose the original problem into several subsets according to the fleet size; then, we relax the nonlinear programs in each subset; later, we select the solutions for those subsets for optimization. Finally, by providing different decomposition plans by rotation, we select from all decomposition plans the best solution with minimum operational cost. By integrating simulation software ProModel and the optimization suite ILOG, we make it possible for the whole decomposition and selection process to run continuously with the optimization programs solved in the background.
520 $a In later chapters of this dissertation, we present another application of optimization. Data Envelopment Analysis (DEA) is used for comparing alike systems by solving a linear program, considering the inputs and outputs of those systems. An application of DEA to the surgeons in a hospital department is studied, and the efficiencies of the surgeons are analyzed. This study analyzes the efficiencies of the surgeons in the department, and provides suggestions to the management group for better distribution of existing resources. DEA can also be used in transportation networks for analyzing the efficiencies of pickup and delivery tasks, and for better distributing the resources, so that the transportation network's cost is reduced and the effectiveness is increased.
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