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A Novel Bi-Encoded NSGA-II for A DRC Scheduling Problem to Minimize the Makespan and Unbalanced Workload

In: Intelligent Engineering and Management for Industry 4.0

Author

Listed:
  • Muhammad Akbar

    (Sophia University
    Bandung Institute of Technology)

  • Takashi Irohara

    (Sophia University)

Abstract

A dual resource-constrained (DRC) scheduling problem of identical parallel semi-automatic machines considers a fewer number of operators who could control setup and unloading tasks. This problem allows the operators to move between machines on the machining time. The objective functions are the makespan and workload smoothness index (WSI) measuring the workload balance between operators related to the social topics in Global Reporting Initiative Reporting Standards (GRI Standards). This problem is complicated because the schedule contains four information, i.e., machine and operator assignments with job and task sequence. This study proposes a novel Bi-encoded Non-Dominated Sorting Genetic Algorithm II (BNSGA-II) as a developed version from the existing Non-Dominated Sorting Genetic Algorithm II (NSGA-II) for solving the DRC scheduling problem. The results show that BNSGA-II equipped with an additional task chromosome could contribute more solutions that NSGA-II could not achieve in the Pareto front for the small and medium-sized problem. It also could generate some new good solutions in the large-sized problem.

Suggested Citation

  • Muhammad Akbar & Takashi Irohara, 2022. "A Novel Bi-Encoded NSGA-II for A DRC Scheduling Problem to Minimize the Makespan and Unbalanced Workload," Springer Books, in: Yong-Hong Kuo & Yelin Fu & Peng-Chu Chen & Calvin Ka-lun Or & George G. Huang & Junwei Wang (ed.), Intelligent Engineering and Management for Industry 4.0, pages 65-76, Springer.
    • Handle: RePEc:spr:sprchp:978-3-030-94683-8_7
    DOI: 10.1007/978-3-030-94683-8_7
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