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.