Lot sizing and scheduling for mixed-model fabrication/assembly systems

This paper is concerned about the simultaneous lot sizing and scheduling problem in pull production systems which are composed of one mixed-model assembly line with limited intermediate buffers and one flexible parts fabrication line with multi-stage parallel machines and limited intermediate buffers. Three objectives are considered simultaneously: minimizing the makespan, minimizing the total overtime and minimizing the total inventory holding costs in the fabrication/assembly system. Since the problem is NP-hard, a hybrid algorithm (GATS) based on genetic algorithm and tabu search is proposed for solving the problem. In this algorithm, a three-values string encoding method is put forward for representing the feasible production sequences for both the assembly and the fabrication lines, and new crossover and mutation operators are designed. The performance of the GATS is compared with the existing genetic algorithm (GA). The computational results show that satisfactory solutions can be obtained by the GATS and it performs better than the GA in terms of solution quality.