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Mathematical Programming Models and ...
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Novoa, Luis J.
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Mathematical Programming Models and Algorithms for Large-Scale Problems in Transportation and Logistics.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Mathematical Programming Models and Algorithms for Large-Scale Problems in Transportation and Logistics./
作者:
Novoa, Luis J.
出版者:
Ann Arbor : ProQuest Dissertations & Theses, : 2016,
面頁冊數:
155 p.
附註:
Source: Dissertations Abstracts International, Volume: 78-03, Section: A.
Contained By:
Dissertations Abstracts International78-03A.
標題:
Transportation planning. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10142751
ISBN:
9781339980171
Mathematical Programming Models and Algorithms for Large-Scale Problems in Transportation and Logistics.
Novoa, Luis J.
Mathematical Programming Models and Algorithms for Large-Scale Problems in Transportation and Logistics.
- Ann Arbor : ProQuest Dissertations & Theses, 2016 - 155 p.
Source: Dissertations Abstracts International, Volume: 78-03, Section: A.
Thesis (Ph.D.)--The George Washington University, 2016.
This item is not available from ProQuest Dissertations & Theses.
The research effort presented in this document focuses on the application of optimization methods to solve two real world problems in the logistics and transportation industry. The first essay looks at the problem of assigning package destinations to secondary sorters within an automated sorting facility, in a way that balances the workload, while explicitly accounting for day-to-day fluctuation in package volumes and adhering to the outbound loading capacities of the workcenters in the facility. In the second essay we develop the theory needed for solving the Resource Constrained Elementary Shortest Path Problem (RCESPP) while accounting for idle time costing. This problem arises as the subproblem for generating columns which, in our case, correspond to feasible routes in a large scale routing problem that accounts for deliveries followed by pickups and that penalizes idle time. Finally, in the third essay we consider the problem of optimizing the daily store servicing routes for major grocery chains, while using real data from a well known chain. We propose to frame the problem as a Capacitated Vehicle Routing Problem with Time Windows that accounts not only for the minimization of travelling costs, but also the minimization of idle time costs. Given the nature of the problem, we propose a reformulation using decomposition techniques which we intend to solve under a customized column generation setup, consisting of several phases.
ISBN: 9781339980171Subjects--Topical Terms:
3423850
Transportation planning.
Subjects--Index Terms:
Labeling algorithms
Mathematical Programming Models and Algorithms for Large-Scale Problems in Transportation and Logistics.
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The research effort presented in this document focuses on the application of optimization methods to solve two real world problems in the logistics and transportation industry. The first essay looks at the problem of assigning package destinations to secondary sorters within an automated sorting facility, in a way that balances the workload, while explicitly accounting for day-to-day fluctuation in package volumes and adhering to the outbound loading capacities of the workcenters in the facility. In the second essay we develop the theory needed for solving the Resource Constrained Elementary Shortest Path Problem (RCESPP) while accounting for idle time costing. This problem arises as the subproblem for generating columns which, in our case, correspond to feasible routes in a large scale routing problem that accounts for deliveries followed by pickups and that penalizes idle time. Finally, in the third essay we consider the problem of optimizing the daily store servicing routes for major grocery chains, while using real data from a well known chain. We propose to frame the problem as a Capacitated Vehicle Routing Problem with Time Windows that accounts not only for the minimization of travelling costs, but also the minimization of idle time costs. Given the nature of the problem, we propose a reformulation using decomposition techniques which we intend to solve under a customized column generation setup, consisting of several phases.
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http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10142751
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