A Mathematical Model and Self-Adaptive NSGA-II for a Multiobjective IPPS Problem Subject to Delivery Time. (24th August 2020)

• Record Type: Journal Article
• Authors: Ba, Li; Yang, Mingshun; Gao, Xinqin; Liu, Yong; Han, Zhoupeng; Xu, Erbao; Li, Yan
• Other Names: Salido Miguel A. Academic Editor.
• Is Part Of: Mathematical problems in engineering. Volume 2020(2020)
• Publication Date: 2020-08-24
• Subjects: Engineering mathematics -- Periodicals; 510.2462
• DOI: 10.1155/2020/6012737
• Languages: English
• ISSNs: 1024-123X

Abstract

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.