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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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
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