DocumentCode
2538285
Title
A Hybrid BPSO Approach for Fuzzy Facility Location Problems with VaR
Author
Wang, Shuming ; Watada, Junzo
Author_Institution
Grad. Sch. of IPS, Waseda Univ., Kitakyushu, Japan
fYear
2010
fDate
13-15 Dec. 2010
Firstpage
43
Lastpage
46
Abstract
In this paper, a fuzzy facility location model with Value at Risk (VaR) is proposed, which is a two-stage fuzzy zero-one integer programming. Since the fuzzy parameters of the location problem are continuous fuzzy variables with an infinite support, the computation of VaR is inherently an infinite-dimensional optimization problem, which can not be solved analytically. In order to solve the model, first of all, the objective function VaR is approximated through discretization method of fuzzy variables. Therefore, the original problem is converted to the task of a finite-dimensional optimization. Then, a hybrid heuristic algorithm integrating binary particle swarm optimization (BPSO), simplex algorithm and the approximation approach is designed to solve the location model. Finally, a numerical example is provided.
Keywords
facility location; fuzzy set theory; integer programming; particle swarm optimisation; VaR; approximation approach; binary particle swarm optimization; continuous fuzzy variable; discretization method; finite dimensional optimization; fuzzy facility location problem; hybrid BPSO approach; hybrid heuristic algorithm; infinite dimensional optimization problem; objective function; simplex algorithm; two stage fuzzy zero one integer programming; value at risk; Algorithm design and analysis; Approximation algorithms; Approximation methods; Computational modeling; Optimization; Particle swarm optimization; Programming; Binary particle swarm optimization; Facility location; Fuzzy variable; Two-stage fuzzy programming; Value at Risk;
fLanguage
English
Publisher
ieee
Conference_Titel
Genetic and Evolutionary Computing (ICGEC), 2010 Fourth International Conference on
Conference_Location
Shenzhen
Print_ISBN
978-1-4244-8891-9
Electronic_ISBN
978-0-7695-4281-2
Type
conf
DOI
10.1109/ICGEC.2010.19
Filename
5715366
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