Hybrid genetic algorithm with adaptive local search scheme for solving multistage-based supply chain problems

The optimal design of supply chain (SC) is a difficult task, if it is composed of the complicated multistage structures with component plants, assembly plants, distribution centers, retail stores and so on. It is mainly because that the multistage-based SC with complicated routes may not be solved using conventional optimization methods. In this study, we propose a genetic algorithm (GA) approach with adaptive local search scheme to effectively solve the multistage-based SC problems.The proposed algorithm has an adaptive local search scheme which automatically determines whether local search technique is used in GA loop or not. In numerical example, two multistage-based SC problems are suggested and tested using the proposed algorithm and other competing algorithms. The results obtained show that the proposed algorithm outperforms the other competing algorithms.