Facility location–allocation problem in random fuzzy environment: Using (α,β) -cost minimization model under the Hurewicz criterion

Abstract

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 $(\alpha ,\beta )$-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 $\lambda$, 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.