Using the Ant Algorithm to Derive Pareto Fronts for Multiobjective Siting of Emergency Service Facilities
Efficient 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.
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Availability:
- Find a library where document is available. Order URL: http://www.trb.org/Main/Public/Blurbs/155479.aspx
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Authors:
- Liu, Nan
- Huang, Bo
- Pan, Xiaohong
- Publication Date: 2005
Language
- English
Media Info
- Media Type: Print
- Features: Figures; References; Tables;
- Pagination: pp 120-129
- Monograph Title: Information Systems and Technology
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Serial:
- Transportation Research Record: Journal of the Transportation Research Board
- Issue Number: 1935
- Publisher: Transportation Research Board
- ISSN: 0361-1981
Subject/Index Terms
- TRT Terms: Algorithms; Alternatives analysis; Decision making; Geographic information systems
- Uncontrolled Terms: Emergency response facility location; Multiobjective optimization; Pareto optimum
- Subject Areas: Highways; Planning and Forecasting; I72: Traffic and Transport Planning;
Filing Info
- Accession Number: 01023229
- Record Type: Publication
- ISBN: 0309094097
- Files: TRIS, TRB, ATRI
- Created Date: Apr 24 2006 1:01PM