Paper Info
Title
Recourse-based facility-location problems in hybrid uncertain environment.
Abstract
The objective of this paper is to study facility-location problems in the presence of a hybrid uncertain environment involving both randomness and fuzziness. A two-stage fuzzy-random facility-location model with recourse (FR-FLMR) is developed in which both the demands and costs are assumed to be fuzzy-random variables. The bounds of the optimal objective value of the two-stage FR-FLMR are derived. As, in general, the fuzzy-random parameters of the FR-FLMR can be regarded as continuous fuzzy-random variables with an infinite number of realizations, the computation of the recourse requires solving infinite second-stage programming problems. Owing to this requirement, the recourse function cannot be determined analytically, and, hence, the model cannot benefit from the use of techniques of classical mathematical programming. In order to solve the location problems of this nature, we first develop a technique of fuzzy-random simulation to compute the recourse function. The convergence of such simulation scenarios is discussed. In the sequel, we propose a hybrid mutation-based binary ant-colony optimization (MBACO) approach to the two-stage FR-FLMR, which comprises the fuzzy-random simulation and the simplex algorithm. A numerical experiment illustrates the application of the hybrid MBACO algorithm. The comparison shows that the hybrid MBACO finds better solutions than the one using other discrete metaheuristic algorithms, such as binary particle-swarm optimization, genetic algorithm, and tabu search.
Year
DOI
Venue
2010
10.1109/TSMCB.2009.2035630
IEEE Transactions on Systems, Man, and Cybernetics, Part B
Keywords
Field
DocType
hybrid uncertain environment,two-stage fuzzy-random facility-location model,fuzzy-random variable,fuzzy-random parameter,hybrid mbaco algorithm,hybrid mbaco,recourse function,continuous fuzzy-random variable,fuzzy-random simulation,two-stage fr-flmr,recourse-based facility-location problem,hybrid mutation-based binary ant-colony,particle swarm optimization,stochastic processes,tabu search,genetic algorithms,mathematical programming,ant colony optimization,convergence,fuzzy set theory,facility location problem,facility location,genetic algorithm,random variables,recourse,mathematical model,simplex algorithm,production systems,computational modeling,profitability
Convergence (routing),Particle swarm optimization,Random variable,Mathematical optimization,Simplex algorithm,Computer science,Facility location problem,Artificial intelligence,Genetic algorithm,Tabu search,Machine learning,Metaheuristic
Journal
Volume
Issue
ISSN
40
4
1941-0492
Citations 
PageRank 
References 
15
0.89
31
Authors
3
Name
Order
Citations
PageRank
Shuming Wang122915.96
Junzo Watada241184.53
W. Pedrycz3139661005.85