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Rough-Cut Capacity Planning in Multi...
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Hartlage, Robert B.
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Rough-Cut Capacity Planning in Multimodal Freight Transportation Networks.
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Rough-Cut Capacity Planning in Multimodal Freight Transportation Networks./
作者:
Hartlage, Robert B.
面頁冊數:
127 p.
附註:
Source: Dissertation Abstracts International, Volume: 74-02(E), Section: B.
Contained By:
Dissertation Abstracts International74-02B(E).
標題:
Operations Research. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3539908
ISBN:
9781267644404
Rough-Cut Capacity Planning in Multimodal Freight Transportation Networks.
Hartlage, Robert B.
Rough-Cut Capacity Planning in Multimodal Freight Transportation Networks.
- 127 p.
Source: Dissertation Abstracts International, Volume: 74-02(E), Section: B.
Thesis (Ph.D.)--Air Force Institute of Technology, 2012.
A main challenge in transporting cargo for United States Transportation Command (USTRANSCOM) is in mode selection or integration. Demand for cargo is time sensitive and must be fulfilled by an established due date. Since these due dates are often inflexible, commercial carriers are used at an enormous expense, in order to fill the gap in organic transportation asset capacity. This dissertation develops a new methodology for transportation capacity assignment to routes based on the Resource Constrained Shortest Path Problem (RCSP). Routes can be single or multimodal depending on the characteristics of the network, delivery timeline, modal capacities, and costs. The difficulty of the RCSP requires use of metaheuristics to produce solutions. An Ant Colony System to solve the RCSP is developed in this dissertation. Finally, a method for generating near Pareto optimal solutions with respect to the objectives of cost and time is developed.
ISBN: 9781267644404Subjects--Topical Terms:
626629
Operations Research.
Rough-Cut Capacity Planning in Multimodal Freight Transportation Networks.
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A main challenge in transporting cargo for United States Transportation Command (USTRANSCOM) is in mode selection or integration. Demand for cargo is time sensitive and must be fulfilled by an established due date. Since these due dates are often inflexible, commercial carriers are used at an enormous expense, in order to fill the gap in organic transportation asset capacity. This dissertation develops a new methodology for transportation capacity assignment to routes based on the Resource Constrained Shortest Path Problem (RCSP). Routes can be single or multimodal depending on the characteristics of the network, delivery timeline, modal capacities, and costs. The difficulty of the RCSP requires use of metaheuristics to produce solutions. An Ant Colony System to solve the RCSP is developed in this dissertation. Finally, a method for generating near Pareto optimal solutions with respect to the objectives of cost and time is developed.
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