A Mathematical Model and Self-Adaptive NSGA-II for a Multiobjective IPPS Problem Subject to Delivery Time

Abstract

Process planning and scheduling are two important components of manufacturing systems. This paper deals with a multiobjective just-in-time integrated process planning and scheduling (MOJIT-IPPS) problem. Delivery time and machine workload are considered to make IPPS problem more suitable for manufacturing environments. The earliness/tardiness penalty, maximum machine workload, and total machine workload are objectives that are minimized. The decoding method is a crucial part that significantly influences the scheduling results. We develop a self-adaptive decoding method to obtain better results. A nondominated sorting genetic algorithm with self-adaptive decoding (SD-NSGA-II) is proposed for solving MOJIT-IPPS. Finally, the model and algorithm are proven through an example. Furthermore, different scale examples are tested to prove the good performance of the proposed method.