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The capacitated minimax location-allocation problem with probabilistic customer locations and border crossing constraints

Minimax facility location allocation is a type of facility problem which is of prime importance for emergency situation, since it directly affects services response times to the customers and cost of transportation. The emergency facility can be a hospital, fire station, or relief room. This thesis...

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Main Author: Mirzapourrezaei, Seyyedali
Format: Thesis
Published: 2013
Subjects:
HD Industries. Land use. Labor
Online Access:http://eprints.utm.my/id/eprint/42225/
http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:77826
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spelling my.utm.422252020-08-18T08:12:01Z http://eprints.utm.my/id/eprint/42225/ The capacitated minimax location-allocation problem with probabilistic customer locations and border crossing constraints Mirzapourrezaei, Seyyedali HD Industries. Land use. Labor Minimax facility location allocation is a type of facility problem which is of prime importance for emergency situation, since it directly affects services response times to the customers and cost of transportation. The emergency facility can be a hospital, fire station, or relief room. This thesis intends to find the optimum or near optimum solution of new emergency facilities which minimize the maximum expected distance between facility and customer area. This study involves a fixed line barrier with some border crossing along it which divides the area into two subregions. Although some studies have recently been accomplished for the case problem in which the customer demand locations are known with certainty, much less attention has been devoted to developing a comprehensive mathematical model for probabilistic customer location in the restricted region that finds the optimum location of emergency facilities and their corresponding allocation clusters. The main focus of this research is developing a mixed integer nonlinear programming model for facility location allocation problem when the location of customers is not exactly defined. The weight of the customer demands has been evaluated based on qualitative and quantitative criteria. Two MINLP solvers, BARON and DICOPT, are applied to find the optimum location of new facilities and compared with each other in terms of solution quality. On task of flood disaster management organization in Amol district in Mazandaran is selected as a case study to demonstrate the proficiency and applicability of the proposed model. The computational results reveal that BARON solver performs better than DICOPT solver and able to achieve the global optimal solution for location of relief rooms. 2013 Thesis NonPeerReviewed Mirzapourrezaei, Seyyedali (2013) The capacitated minimax location-allocation problem with probabilistic customer locations and border crossing constraints. Masters thesis, Universiti Teknologi Malaysia, Faculty of Mechanical Engineering. http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:77826
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic HD Industries. Land use. Labor
spellingShingle HD Industries. Land use. Labor
Mirzapourrezaei, Seyyedali
The capacitated minimax location-allocation problem with probabilistic customer locations and border crossing constraints
description Minimax facility location allocation is a type of facility problem which is of prime importance for emergency situation, since it directly affects services response times to the customers and cost of transportation. The emergency facility can be a hospital, fire station, or relief room. This thesis intends to find the optimum or near optimum solution of new emergency facilities which minimize the maximum expected distance between facility and customer area. This study involves a fixed line barrier with some border crossing along it which divides the area into two subregions. Although some studies have recently been accomplished for the case problem in which the customer demand locations are known with certainty, much less attention has been devoted to developing a comprehensive mathematical model for probabilistic customer location in the restricted region that finds the optimum location of emergency facilities and their corresponding allocation clusters. The main focus of this research is developing a mixed integer nonlinear programming model for facility location allocation problem when the location of customers is not exactly defined. The weight of the customer demands has been evaluated based on qualitative and quantitative criteria. Two MINLP solvers, BARON and DICOPT, are applied to find the optimum location of new facilities and compared with each other in terms of solution quality. On task of flood disaster management organization in Amol district in Mazandaran is selected as a case study to demonstrate the proficiency and applicability of the proposed model. The computational results reveal that BARON solver performs better than DICOPT solver and able to achieve the global optimal solution for location of relief rooms.
format Thesis
author Mirzapourrezaei, Seyyedali
author_facet Mirzapourrezaei, Seyyedali
author_sort Mirzapourrezaei, Seyyedali
title The capacitated minimax location-allocation problem with probabilistic customer locations and border crossing constraints
title_short The capacitated minimax location-allocation problem with probabilistic customer locations and border crossing constraints
title_full The capacitated minimax location-allocation problem with probabilistic customer locations and border crossing constraints
title_fullStr The capacitated minimax location-allocation problem with probabilistic customer locations and border crossing constraints
title_full_unstemmed The capacitated minimax location-allocation problem with probabilistic customer locations and border crossing constraints
title_sort capacitated minimax location-allocation problem with probabilistic customer locations and border crossing constraints
publishDate 2013
url http://eprints.utm.my/id/eprint/42225/
http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:77826
_version_ 1677781069891371008
score 13.211869

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