A discrete location model with fuzzy accessibility measures
Fuzzy Sets and Systems
Uncapacitated plant location-allocation problems with price sensitive stochastic demands
Computers and Operations Research
Bi-criteria multi facility location problem in fuzzy environment
Fuzzy Sets and Systems
Chance constrained programming with fuzzy parameters
Fuzzy Sets and Systems
A note on chance constrained programming with fuzzy coefficients
Fuzzy Sets and Systems
Minimax chance constrained programming models for fuzzy decision systems
Information Sciences: an International Journal
Theory and Practice of Uncertain Programming
Theory and Practice of Uncertain Programming
New stochastic models for capacitated location-allocation problem
Computers and Industrial Engineering
Dependent-chance programming with fuzzy decisions
IEEE Transactions on Fuzzy Systems
Expected value of fuzzy variable and fuzzy expected value models
IEEE Transactions on Fuzzy Systems
Convergent results about the use of fuzzy simulation in fuzzy optimization problems
IEEE Transactions on Fuzzy Systems
Heuristic solution of the multisource Weber problem as a p-median problem
Operations Research Letters
Fuzzy data envelopment analysis (DEA): Model and ranking method
Journal of Computational and Applied Mathematics
Computers & Mathematics with Applications
Survey: Facility location dynamics: An overview of classifications and applications
Computers and Industrial Engineering
A robust critical path in an environment with hybrid uncertainty
Applied Soft Computing
Information Sciences: an International Journal
A random fuzzy minimum spanning tree problem through a possibility-based value at risk model
Expert Systems with Applications: An International Journal
Hi-index | 0.09 |
Facility location-allocation (FLA), which has been proved to be a valuable method in siting service facility, is widely used in real life, such as emergency service systems, telecommunication net works, public services, etc. Many researchers have studied the FLA problem in a deterministic, stochastic or fuzzy environment. However, those models cannot satisfy various customers' demands in some cases. Thus, this paper considers the FLA problem under random fuzzy environment using (@a,@b)-cost minimization model under the Hurwicz criterion. It will be proved that this model can deal with various FLA problems in random, fuzzy and random fuzzy environments. By varying the value @l, it can balance the optimistic level of the decision makers. For solving the random fuzzy model efficiently, the simplex algorithm, random fuzzy simulation and genetic algorithm are integrated to produce a hybrid intelligent algorithm. Finally, a numerical example is presented for illustration.