A hybrid population-based algorithm for solving the fuzzy capacitated maximal covering location problem
Résumé
In this paper, we study the fuzzy capacitated maximal covering location problem, where a hybrid population -based algorithm is proposed to solve it. An instance of the problem is represented by a set of customers in a given network with their distances and such that the coverage degree of facilities and the distance between customers are fuzzy. Its goal is to open (select) a subset of facilities to be located on customers such that the coverage of customers should be maximized. Two versions of a hybrid population-based algorithm are designed for tackling the aforementioned problem: (i) a modified grey wolf optimizer combined with exploration and exploitation strategies, and (ii) a modified grey wolf optimizer combined with a series of local searches and an upper bound delimiting wolf movements. Each version of the method enhances the quality of the solutions belonging to the current population by adding a series of local searches. Further, the exploration strategy is based upon the drop/rebuild operator for jumping from the current region to unvisited ones. Finally, the behavior of the proposed method is evaluated on a set of benchmark instances of the literature, where its provided results are compared to those reached by more recent methods of the literature and the state-of-the-art Cplex solver. Encouraging results have been obtained.