Hybrid Genetic Algorithm for Production/Distribution System in Supply Chain

This research is concerned with logistic system design considering production/distribution planning in the view of multi-stage structure. The design tasks of this problem involve the choice of the facilities (plants and distribution centers (DCs)) to be opened, and the production/distribution network design to satisfy the demand with minimum cost. Since this problem is known as one of the NP-hard problems, we propose a heuristic algorithm for solving it. The proposed method, called hybrid-spanning, tree-based genetic algorithm (hst-GA), utilizes the Prüfer number, which is known to be an efficient way to represent various network problems. In order to improve the performance of the proposed method, we develop a local search technique, called displacing Prüfer number, and adopt the concept of a fuzzy logic controller (FLC) to dynamically control the GA parameters. We implement the proposed method on several test problems and compare the results with those of other traditional methods and LINDO. These comparisons demonstrate that the proposed method out-performed other traditional methods.