A genetic algorithm heuristic approach to general outsourcing capacitated production planning problems

This paper addresses a dynamic capacitated production planning (CPP) problem with consideration of outsourcing. Specifically, the outsourcing problem considered in this paper has the following features: (1) all demands are met by production or outsourcing without postponement or backlog, (2) production, inventory, and outsourcing levels all have a limit, and (3) the cost functions are considered arbitrarily and time-varying. These features come together, leading to a so-called general outsourcing CPP problem. In our previous work, an algorithm with pseudo-polynomial time complexity was developed, which includes a formation of a feasible solution region and then a search procedure using dynamic programming techniques. Due to the computational complexity with such an approach, only small and medium problems can be solved in a practical sense. In this paper, we present a genetic algorithm (GA) approach to the same problem. The novelty of this GA approach is that the idea of the feasible solution region is used as a heuristic to guide the searching process. We present a computational experiment to show the effectiveness of the proposed approach.