A solution method to maximal covering location problem based on chemical reaction optimization (CRO) algorithm.

The maximal covering location problem refers to the problem of finding an optimal placement of given number of facilities to a network. The objective is to maximize the total demands of the covered population within some constraints. Several metaheuristic approaches were proposed to solve the problem as it is an NP hard problem. In this article, we have proposed a chemical reaction optimization (CRO)-based approach to solve MCLP. CRO is a metaheuristic based on population to solve optimization problems. We are proposing a method to solve MCLP by redesigning four fundamental operators of CRO. Sometimes the solutions get trapped into local maxima, so an additional repair operator is also designed to find optimal solutions. The proposed algorithm is tested for both small and large scales of instances of datasets, which include benchmark as well as random ones. The proposed method gives best percentage of coverage results in 91.60% of instances, and for the remaining 8.40% of instances it produces results with average error value 0.10% which is very close to the optimal value. Nevertheless, the proposed method performs very well in terms of computational time for all test instances (100%) on all datasets compared to state-of-the-art method (Atta_GA). Wilcoxon signed-rank test has been performed on the results of the proposed method to observe the statistical significance. For both real-world and random instances, the results of the statistical test are significant. [ABSTRACT FROM AUTHOR]