A fuzzy multi-objective programming for optimization of fire station locations through genetic algorithms

Location of fire stations is an important factor in its fire protection capability. This paper aims to determine the optimal location of fire station facilities. The proposed method is the combination of a fuzzy multi-objective programming and a genetic algorithm. The original fuzzy multiple objecti...

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Veröffentlicht in:European journal of operational research Jg. 181; H. 2; S. 903 - 915
Hauptverfasser: Yang, Lili, Jones, Bryan F., Yang, Shuang-Hua
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Amsterdam Elsevier B.V 01.09.2007
Elsevier
Elsevier Sequoia S.A
Schriftenreihe:European Journal of Operational Research
Schlagworte:
Applied sciences
Decision making models
Decision theory. Utility theory
Exact sciences and technology
Fire protection
Fire stations
Fuzzy logic
Fuzzy programming
Genetic algorithm
Genetic algorithms
Location
Logistics
Multi-objective programming
Operational research and scientific management
Operational research. Management science
Optimization
Optimization algorithms
Studies
Fire stations
Fuzzy programming
Multi-objective programming
Genetic algorithm
Location
Decision making
Multiobjective programming
Fire station
Fire protection
Modeling
Location problem
Optimization
Facility location
Fuzzy logic
Uncertain system
Fire
Minimax method
Fuzzy decision
ISSN:0377-2217, 1872-6860
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Zusammenfassung:Location of fire stations is an important factor in its fire protection capability. This paper aims to determine the optimal location of fire station facilities. The proposed method is the combination of a fuzzy multi-objective programming and a genetic algorithm. The original fuzzy multiple objectives are appropriately converted to a single unified ‘min–max’ goal, which makes it easy to apply a genetic algorithm for the problem solving. Compared with the existing methods of fire station location our approach has three distinguish features: (1) considering fuzzy nature of a decision maker (DM) in the location optimization model; (2) fully considering the demands for the facilities from the areas with various fire risk categories; (3) being more understandable and practical to DM. The case study was based on the data collected from the Derbyshire fire and rescue service and used to illustrate the application of the method for the optimization of fire station locations.
Bibliographie:SourceType-Scholarly Journals-1
ObjectType-Feature-1
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ISSN:0377-2217
1872-6860
DOI:10.1016/j.ejor.2006.07.003