Abstract
Recently, we have concerned the strategic optimization on logistic network design and developed an efficient two-level solution method. To cope with extremely large-scale problems, in this paper, we propose an extended algorithm for parallel computing for the two-level algorithms that utilizes the analogy between the algorithm and the master-worker configuration of PC cluster. To enhance the efficiency, we adopted a population-based algorithm like particle swarm optimization (PSO) and developed a new discrete algorithm of PSO to deal with the binary decision variables standing for open or close of the DC sites. Then, we have developed a parallel procedure that can make the over head for the parallel computing very small, and finally bring about high performance for the parallel computing suitable for the present goals and circumstances. Through numerical experiments, we confirmed the effectiveness of parallelization from a few aspects that characterize the proposed method.
