Configuring a seru production system to match supply with volatile demand

In recent years, volatile markets have given rise to a new production system, seru production system, which has been widely utilized in the Asian electronics industry and considered as the next generation of lean production. This paper focuses on the configuration of a seru production system considering that (1) serus are physically reconfigurable rather than fixed and (2) workers have different skill ranges and processing velocities. A mathematical model, whose objectives are to minimize the total completion time and to minimize the total labor cost, is constructed. An improved multiobjective algorithm that combines a multiobjective genetic algorithm, differential evolutionary algorithm and conflict-factor-based mutation operator is proposed in this paper. Computational experiments show that our proposed algorithm outperforms classic scheduling heuristics and well-known algorithms.