Hybrid self-adaptive-velocity particle swarm optimisation-Cooper heuristic for the facility location allocation problem in Jakarta

Abstract

By solving the facility location problem, one can locate facilities under constraints such that customers are served efficiently. This is a case study of Logistic Company X, which will build new depots in Jakarta, Indonesia. The depots must be located in an industrial and warehousing area. A proposed continuous uncapacitated location allocation model is applied to solve the problem, which has many bounded polygonal zones as constraints. The objective of this study is to determine the number of depots that should be opened in the defined areas, and the number of customers that each depot can serve, such that the total cost, including transportation cost and setup cost, are minimised. The proposed self-adaptive-velocity particle swarm optimisation (SAVPSO) algorithm with the Cooper heuristic algorithm (hybrid SAVPSO) is used to solve the problem. Numerical results indicate that the proposed algorithm is effective and gives better solutions than a generic algorithm and the non-hybrid SAVPSO under various test conditions. The hypothesis test also demonstrates that the performance of the hybrid SAVPSO is better than that of the SAVPSO. Finally, sensitivity analysis is also performed to identify the problem's sensitive variables to support decision-making in this warehouse location problem.