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Article: GIS and genetic algorithms for HAZMAT route planning with security considerations

TitleGIS and genetic algorithms for HAZMAT route planning with security considerations
Authors
Issue Date2004
Citation
International Journal of Geographical Information Science, 2004, v. 18, n. 8, p. 769-787 How to Cite?
AbstractSingapore is the third largest oil-refining centre in the world, with a large petrochemical hub located at Jurong Island. In view of the increasing concern for transportation security, there is an urgent need to improve the way trucks carrying hazardous materials (HAZMATs) are being routed on urban and suburban road networks. Routing of such vehicles should not only ensure the safety of travelers in the network but also consider the risk of the HAZMAT being used as weapon of mass destruction. This paper explores a novel approach to evaluating the risk of HAZMAT transportation by integrating Geographic Information Systems (GISs) and Genetic Algorithms (GAs). A set of evaluation criteria that are used to route the HAZMAT vehicles was identified and assessed. The criteria considered are related to safety, costs and, more importantly, security. A GIS was employed to quantify the factors on each link in the network that contribute to the evaluation criteria for a possible route, while a GA was applied to efficiently determine the weights of the different factors in the hierarchical form, allowing for the computation of the relative total costs of the alternate routes. Therefore, each route can be quantified by a generalized cost function from which the suitability of the routes for HAZMAT transportation can be compared. The proposed route evaluation method was demonstrated on a typical portion of the road network in Singapore. © 2004 Taylor & Francis Ltd.
Persistent Identifierhttp://hdl.handle.net/10722/329995
ISSN
2023 Impact Factor: 4.3
2023 SCImago Journal Rankings: 1.436
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorHuang, Bo-
dc.contributor.authorCheu, Ruey Long-
dc.contributor.authorLiew, Yong Seng-
dc.date.accessioned2023-08-09T03:37:03Z-
dc.date.available2023-08-09T03:37:03Z-
dc.date.issued2004-
dc.identifier.citationInternational Journal of Geographical Information Science, 2004, v. 18, n. 8, p. 769-787-
dc.identifier.issn1365-8816-
dc.identifier.urihttp://hdl.handle.net/10722/329995-
dc.description.abstractSingapore is the third largest oil-refining centre in the world, with a large petrochemical hub located at Jurong Island. In view of the increasing concern for transportation security, there is an urgent need to improve the way trucks carrying hazardous materials (HAZMATs) are being routed on urban and suburban road networks. Routing of such vehicles should not only ensure the safety of travelers in the network but also consider the risk of the HAZMAT being used as weapon of mass destruction. This paper explores a novel approach to evaluating the risk of HAZMAT transportation by integrating Geographic Information Systems (GISs) and Genetic Algorithms (GAs). A set of evaluation criteria that are used to route the HAZMAT vehicles was identified and assessed. The criteria considered are related to safety, costs and, more importantly, security. A GIS was employed to quantify the factors on each link in the network that contribute to the evaluation criteria for a possible route, while a GA was applied to efficiently determine the weights of the different factors in the hierarchical form, allowing for the computation of the relative total costs of the alternate routes. Therefore, each route can be quantified by a generalized cost function from which the suitability of the routes for HAZMAT transportation can be compared. The proposed route evaluation method was demonstrated on a typical portion of the road network in Singapore. © 2004 Taylor & Francis Ltd.-
dc.languageeng-
dc.relation.ispartofInternational Journal of Geographical Information Science-
dc.titleGIS and genetic algorithms for HAZMAT route planning with security considerations-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1080/13658810410001705307-
dc.identifier.scopuseid_2-s2.0-9744275275-
dc.identifier.volume18-
dc.identifier.issue8-
dc.identifier.spage769-
dc.identifier.epage787-
dc.identifier.isiWOS:000225296700003-

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