Heuristic genetic algorithm for capacitated production planning problems with batch processing and remanufacturing

In this paper, we analyze a version of the capacitated dynamic lot-sizing problem with substitutions and return products. Both batch manufacturing and batch remanufacturing are considered within the framework of deterministic time-varying demands in a finite time horizon, where the option of emergency procurement/outsourcing subject to a subcontract is also allowed. Setup costs are taken into account when batch manufacturing or batch remanufacturing takes place. We first apply a genetic algorithm to determine all periods requiring setups for batch manufacturing and batch remanufacturing, then develop a dynamic programming approach to provide the optimal solution to determine how many new products are manufactured or return products are remanufactured in each of these periods. The objective is to minimize the total cost, including batch manufacturing, batch remanufacturing, emergency procurement, holding and setup costs. Numerical examples illustrate the effectiveness of the approach.