A hybrid Approach for Logistics Center Location Using Discrete Particle Swarm Optimization

The location selection of logistics center (LC) described as the mixed-integer linear model is one of difficult combinational optimization problems. In this paper, we propose a hybrid particle swarm optimization (PSO) algorithm, extended from discrete PSO, for solving the mixed-integer nonlinear optimization problem. In the proposed algorithm, the particle and the velocity are redefined and the sequential quadratic programming (SQP) is also applied to cope with nonlinear inequality constraint in model. Furthermore, we incorporate the Tabu search method which can enhance the seek ability in exploration into proposed algorithm, called PSO-Tabu. Experimental results reveal that the proposed approach is a practicable technique for solving the logistics center location problem.