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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Abstract	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.
AbstractList	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. [PUBLICATION ABSTRACT] 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.
Author	Jones, Bryan F. Yang, Lili Yang, Shuang-Hua
Author_xml	– sequence: 1 givenname: Lili surname: Yang fullname: Yang, Lili email: L.yang@lboro.ac.uk organization: Business School, Loughborough University, Loughborough, Leicestershire LE11 3TU, UK – sequence: 2 givenname: Bryan F. surname: Jones fullname: Jones, Bryan F. organization: Applied Computing Department, The University of Derby, Derby DE22 1GB, UK – sequence: 3 givenname: Shuang-Hua surname: Yang fullname: Yang, Shuang-Hua organization: Computer Science Department, Loughborough University, Loughborough, Leicestershire LE11 3TU, UK
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Keywords	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
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Snippet	Location of fire stations is an important factor in its fire protection capability. This paper aims to determine the optimal location of fire station...
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SubjectTerms	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
Title	A fuzzy multi-objective programming for optimization of fire station locations through genetic algorithms
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