Hazmats Transportation Network Design Model with Emergency Response under Complex Fuzzy Environment
A bilevel optimization model for a hazardous materials transportation network design is presented which considers an emergency response teams location problem. On the upper level, the authority designs the transportation network to minimize total transportation risk. On the lower level, the carriers...
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2013-01-01
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Series: | Mathematical Problems in Engineering |
Online Access: | http://dx.doi.org/10.1155/2013/517372 |
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doaj-f21db1ad1d1e4c868de3008d9ada61672020-11-24T22:01:27ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472013-01-01201310.1155/2013/517372517372Hazmats Transportation Network Design Model with Emergency Response under Complex Fuzzy EnvironmentJiuping Xu0Jun Gang1Xiao Lei2State Key Laboratory of Hydraulics and Mountain River Engineering, Sichuan University, Chengdu 610064, ChinaUncertainty Decision-Making Laboratory, Sichuan University, Chengdu 610064, ChinaChina Three Gorges Corporation, Yichang 443002, ChinaA bilevel optimization model for a hazardous materials transportation network design is presented which considers an emergency response teams location problem. On the upper level, the authority designs the transportation network to minimize total transportation risk. On the lower level, the carriers first choose their routes so that the total transportation cost is minimized. Then, the emergency response department locates their emergency service units so as to maximize the total weighted arc length covered. In contrast to prior studies, the uncertainty associated with transportation risk has been explicitly considered in the objective function of our mathematical model. Specifically, our research uses a complex fuzzy variable to model transportation risk. An improved artificial bee colony algorithm with priority-based encoding is also applied to search for the optimal solution to the bilevel model. Finally, the efficiency of the proposed model and algorithm is evaluated using a practical case and various computing attributes.http://dx.doi.org/10.1155/2013/517372 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Jiuping Xu Jun Gang Xiao Lei |
spellingShingle |
Jiuping Xu Jun Gang Xiao Lei Hazmats Transportation Network Design Model with Emergency Response under Complex Fuzzy Environment Mathematical Problems in Engineering |
author_facet |
Jiuping Xu Jun Gang Xiao Lei |
author_sort |
Jiuping Xu |
title |
Hazmats Transportation Network Design Model with Emergency Response under Complex Fuzzy Environment |
title_short |
Hazmats Transportation Network Design Model with Emergency Response under Complex Fuzzy Environment |
title_full |
Hazmats Transportation Network Design Model with Emergency Response under Complex Fuzzy Environment |
title_fullStr |
Hazmats Transportation Network Design Model with Emergency Response under Complex Fuzzy Environment |
title_full_unstemmed |
Hazmats Transportation Network Design Model with Emergency Response under Complex Fuzzy Environment |
title_sort |
hazmats transportation network design model with emergency response under complex fuzzy environment |
publisher |
Hindawi Limited |
series |
Mathematical Problems in Engineering |
issn |
1024-123X 1563-5147 |
publishDate |
2013-01-01 |
description |
A bilevel optimization model for a hazardous materials transportation network design is presented which considers an emergency response teams location problem. On the upper level, the authority designs the transportation network to minimize total transportation risk. On the lower level, the carriers first choose their routes so that the total transportation cost is minimized. Then, the emergency response department locates their emergency service units so as to maximize the total weighted arc length covered. In contrast to prior studies, the uncertainty associated with transportation risk has been explicitly considered in the objective function of our mathematical model. Specifically, our research uses a complex fuzzy variable to model transportation risk. An improved artificial bee colony algorithm with priority-based encoding is also applied to search for the optimal solution to the bilevel model. Finally, the efficiency of the proposed model and algorithm is evaluated using a practical case and various computing attributes. |
url |
http://dx.doi.org/10.1155/2013/517372 |
work_keys_str_mv |
AT jiupingxu hazmatstransportationnetworkdesignmodelwithemergencyresponseundercomplexfuzzyenvironment AT jungang hazmatstransportationnetworkdesignmodelwithemergencyresponseundercomplexfuzzyenvironment AT xiaolei hazmatstransportationnetworkdesignmodelwithemergencyresponseundercomplexfuzzyenvironment |
_version_ |
1725839394944843776 |