An Efficient Hybrid Particle Swarm Optimization Algorithm for Solving the Uncapacitated Continuous Location-Allocation Problem

Location-allocation problems are a class of complicated optimization problems that determine the location of facilities and the allocation of customers to the facilities. In this paper, the uncapacitated continuous location-allocation problem is considered, and a particle swarm optimization approach, which has not previously been applied to this problem, is presented. Two algorithms including classical and hybrid particle swarm optimization algorithms are developed. Local optima of the problem are obtained by two local search heuristics that exist in the literature. These algorithms are combined with particle swarm optimization to construct an efficient hybrid approach. Many large-scale problems are used to measure the effectiveness and efficiency of the proposed algorithms. Our results are compared with the best algorithms in the literature. The experimental results show that the hybrid PSO produces good solutions, is more efficient than the classical PSO, and is competitive with the best results from the literature. Additionally, the proposed hybrid PSO found better solutions for some instances than did the best known solutions in the literature.