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Conference Paper: Using the ant algorithm to derive pareto fronts for multiobjective siting of emergency service facilities

TitleUsing the ant algorithm to derive pareto fronts for multiobjective siting of emergency service facilities
Authors
Issue Date2005
Citation
Transportation Research Record, 2005, n. 1935, p. 120-129 How to Cite?
AbstractEfficient and timely response during accidents has received increased attention from practitioners and researchers. The siting of emergency service facilities (ESFs) plays a crucial role in determining the efficiency of safety protection and emergency response. This paper explores a novel multiobjective ant algorithm for the siting of ESFs. With the aid of the geographic information system, the algorithm finds a population of solutions, uses Pareto ranking to sort these solutions, and derives the Pareto front. It is demonstrated that the algorithm successfully captures a pool of nondominated solutions and thereby provides decision makers with a set of alternative solutions. The case study also demonstrates how decision makers may choose one "best" solution from the pool according to their preference or determinant criteria.
Persistent Identifierhttp://hdl.handle.net/10722/330070
ISSN
2023 Impact Factor: 1.6
2023 SCImago Journal Rankings: 0.543

 

DC FieldValueLanguage
dc.contributor.authorLiu, Nan-
dc.contributor.authorHuang, Bo-
dc.contributor.authorPan, Xiaohong-
dc.date.accessioned2023-08-09T03:37:34Z-
dc.date.available2023-08-09T03:37:34Z-
dc.date.issued2005-
dc.identifier.citationTransportation Research Record, 2005, n. 1935, p. 120-129-
dc.identifier.issn0361-1981-
dc.identifier.urihttp://hdl.handle.net/10722/330070-
dc.description.abstractEfficient and timely response during accidents has received increased attention from practitioners and researchers. The siting of emergency service facilities (ESFs) plays a crucial role in determining the efficiency of safety protection and emergency response. This paper explores a novel multiobjective ant algorithm for the siting of ESFs. With the aid of the geographic information system, the algorithm finds a population of solutions, uses Pareto ranking to sort these solutions, and derives the Pareto front. It is demonstrated that the algorithm successfully captures a pool of nondominated solutions and thereby provides decision makers with a set of alternative solutions. The case study also demonstrates how decision makers may choose one "best" solution from the pool according to their preference or determinant criteria.-
dc.languageeng-
dc.relation.ispartofTransportation Research Record-
dc.titleUsing the ant algorithm to derive pareto fronts for multiobjective siting of emergency service facilities-
dc.typeConference_Paper-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.3141/1935-14-
dc.identifier.scopuseid_2-s2.0-33646434240-
dc.identifier.issue1935-
dc.identifier.spage120-
dc.identifier.epage129-

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