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Scheduling Problem for Allocating Worker with Class-Type Skill in JSP by Hybrid Genetic Algorithm

  • Kenichi IdaEmail author
  • Daiki Takano
  • Mitsuo Gen
Conference paper
Part of the Lecture Notes on Multidisciplinary Industrial Engineering book series (LNMUINEN)

Abstract

Scheduling in manufacturing systems is one of the most important and complex combinatorial optimization problems, where it can have a major impact on the productivity of a production process. Moreover, most of manufacturing scheduling models fall into the class of NP-hard combinatorial problems. In a real world manufacturing system, a plurality of worker who operates the machine exists, depending on the skill level by the workers for each machine and working time is different even if same work on the same machine in job-shop scheduling problem (JSP). Therefore, it is taking to account for differences in working time by the worker is scheduling problem with worker allocation. In this paper, in order to approach the more realistic model by dividing into several class workers and to determine the skill level for each machine for each class worker, we propose a new model that introduced the concept of class-type skill and demonstrate the effectiveness of the computational result by Hybrid Genetic Algorithm.

Keywords

Job-shop scheduling problem (JSP) Scheduling problem for allocating worker (SPAW) Class-type skill Hybrid genetic algorithm 

Notes

Acknowledgements

This research work is supported by the Grant-in-Aid for Scientific Research (C) of Japan Society of Promotion of Science (JSPS): No. 15K00357.

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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.Graduate School of EngineeringMaebashi Institute of TechnologyMaebashiJapan
  2. 2.Fuzzy Logic Systems Institute and Tokyo University of ScienceTokyoJapan

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