Applying a hybrid particle swarm optimization_Tabu search algorithm to a facility location case in Jakarta

Abstract

The hierarchical facility location problem (HFLP) is defined as determining the location of facilities in such a way that high-level facilities can serve the facilities in low-level efficiently. In this paper, a mixed integer programming model for the HFLP with the flow capacity constraint is proposed. An approach hybrided PSO and Tabu search (TS) (HPSO-TS) is proposed to solve the HFLP. The objective is to minimize overall demand-weighted distance travel, facility operating costs, and flow assignment costs. This method transforms PSO particles representing various dimensions of the attributes into a Tabu priority list and then constructs the assignment networks. The performance of the proposed algorithm is compared with branch-and-bound algorithm, a genetic algorithm, and classical PSO. Numerical results show that the performance of the proposed algorithm is better than those with exact methods when solving such problems. Finally, the proposed algorithm is applied to solve a case company in Jakarta.

Keywords:

• Hierarchical facility location problem
• particle swarm optimization
• mixed integer linear programming
• facility location problem