Genetic algorithm-based integrated production planning considering manufacturing partners

This paper deals with an integrated production planning problem in the presence of manufacturing partners. In this environment, although most of the products and parts are produced in local plants, they can also be purchased from any desirable manufacturing partners at reasonable costs. The objective of this study is to provide efficient integrated production plans for both local plants with finite production capacity and manufacturing partners, while minimizing the total production costs. For solving this problem, we formulated an integrated production planning problem by modifying a multi-level lot-sizing (MLLS) problem, and proposed an efficient genetic-algorithm-based heuristic for minimizing the costs of production, inventory, and subcontracting with manufacturing partners. The proposed heuristic consists of a unique chromosome structure, a chromosome-generation method, and genetic operators. The experimental analysis shows that the proposed heuristic generates quite good solutions at low computational costs, in comparison with a commercial optimization package.