TY - JOUR
T1 - Capacitated two-stage facility location problem with fuzzy costs and demands
AU - Wang, Shuming
AU - Watada, Junzo
PY - 2013
Y1 - 2013
N2 - In this study, we develop a two-stage capacitated facility location model with fuzzy costs and demands. The proposed model is a task of 0-1 integer two-stage fuzzy programming problem. In order to solve the problem, we first apply an approximation approach to estimate the objective function (with fuzzy random parameters) and prove the convergence of the approach. Then, we design a hybrid algorithm which integrates the approximation approach, neural network and particle swarm optimization, to solve the proposed facility location problem. Finally, a numerical example is provided to test the hybrid algorithm.
AB - In this study, we develop a two-stage capacitated facility location model with fuzzy costs and demands. The proposed model is a task of 0-1 integer two-stage fuzzy programming problem. In order to solve the problem, we first apply an approximation approach to estimate the objective function (with fuzzy random parameters) and prove the convergence of the approach. Then, we design a hybrid algorithm which integrates the approximation approach, neural network and particle swarm optimization, to solve the proposed facility location problem. Finally, a numerical example is provided to test the hybrid algorithm.
KW - Fuzzy variable
KW - Location
KW - Neural network
KW - Particle swarm optimization
KW - Two-stage fuzzy programming
UR - http://www.scopus.com/inward/record.url?scp=84872350789&partnerID=8YFLogxK
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U2 - 10.1007/s13042-012-0073-0
DO - 10.1007/s13042-012-0073-0
M3 - Article
AN - SCOPUS:84872350789
SN - 1868-8071
VL - 4
SP - 65
EP - 74
JO - International Journal of Machine Learning and Cybernetics
JF - International Journal of Machine Learning and Cybernetics
IS - 1
ER -