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Modified Network Simplex Method to Solve a Sheltering Network Planning and Management Problem

This dissertation considers sheltering network planning and operations for natural disaster preparedness and responses with a two-stage stochastic program. The first phase of the network design decides the locations, capacities and held resources of new permanent shelters. Both fixed costs for building a new permanent shelter and variable costs based on capacity are considered. Under each disaster scenario featured by the evacuee demand and transportation network condition, the flows of evacuees and resources to shelters, including permanent and temporary ones, are determined in the second stage to minimize the transportation and shortage/surplus costs. Typically, a large number of scenarios are involved in the problem and cause a huge computational burden. The L-shaped algorithm is applied to decompose the problem into the scenario level with each sub-problem as a linear program. The Sheltering Network Planning and Operation Problem considered in this dissertation also has a special structure in the second-stage sub-problem that is a minimum cost network flow problem with equal flow side constraints. Therefore, the dissertation also takes advantages of the network simplex method to solve the response part of the problem in order to solve the problem more efficiently. This dissertation investigates the extending application of special minimum cost equal flow problem. A case study for preparedness and response to hurricanes in the Gulf Coast region of the United States is conducted to demonstrate the usage of the model including how to define scenarios and cost structures. The numerical experiment results also verify the fast convergence of the L-shaped algorithm for the model.

Identiferoai:union.ndltd.org:MSSTATE/oai:scholarsjunction.msstate.edu:td-4170
Date09 December 2011
CreatorsLi, Lingfeng
PublisherScholars Junction
Source SetsMississippi State University
Detected LanguageEnglish
Typetext
Formatapplication/pdf
SourceTheses and Dissertations

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