NDLI: Fuzzy random facility location problems with recourse

Content Provider	IEEE Xplore Digital Library
Author	Shuming Wang Watada, J. Pedrycz, W.
Copyright Year	2009
Description	Author affiliation: Graduate School of Information, Production and Systems, Waseda University, Kitakyushu 808-0135, Fukuoka, Japan (Shuming Wang; Watada, J.) \|\| Department of Electrical & Computer Engineering, University of Alberta, Edmonton, T6G 2G7, Canada and Systems Research Institute, Polish Academy of Sciences Warsaw, Poland (Pedrycz, W.)
Abstract	The objective of this paper is to study facility location problems under a hybrid uncertain environment involving randomness and fuzziness. A two-stage fuzzy random facility location model with recourse is developed in which the demands and the costs are assumed to be fuzzy random variables. As in general the fuzzy random parameters in the model can be regarded as continuous fuzzy random variables with infinite realizations, the computation of the recourse requires solving infinite second-stage programming problems. Owing to this fact, the recourse function cannot be calculated analytically, which implies that the model cannot benefit from the use of methods of classical mathematical programming. In order to solve the location problems of this nature, we first develop techniques of fuzzy random simulation. In the sequel, by combining the fuzzy random simulation, simplex algorithm and binary particle swarm optimization (BPSO), a hybrid algorithm is proposed to solve the two-stage fuzzy random facility location model. Finally, an illustrative numerical example is provided.
Starting Page	1846
Ending Page	1851
File Size	179912
Page Count	6
File Format	PDF
ISBN	9781424427932
ISSN	1062922X
DOI	10.1109/ICSMC.2009.5346731
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-10-11
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Random variables Stochastic processes Costs Particle swarm optimization Cybernetics USA Councils Fuzzy systems Production systems Humans Statistics Binary particle swarm optimization Facility location Two-stage fuzzy random programming Recourse Fuzzy random variable
Content Type	Text
Resource Type	Article

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