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An improved NSGA-II algorithm for the dual-resource constrained multi-objective flexible job shop scheduling problem (DRCMOFJSP) is proposed, with improved encoding and decoding and an optimized genetic evolution strategy. In addition, the problem of multi-objective optimization is solved by using non-dominated ordering and congestion computation. Experimental results show that the proposed method outperforms the MOEA/D algorithm in scheduling efficiency.

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An Improved NSGA-II Algorithm for Dual-Resource Constrained Multi-Objective Flexible Job Shop Scheduling Problems

  • 会议论文

  • 发表日期：

    2025年

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  • Chengwan Li,
  • Lixin Lu,
  • Guiqin Li,
  • Peter Mitrouchev

摘要

An improved NSGA-II algorithm for the dual-resource constrained multi-objective flexible job shop scheduling problem (DRCMOFJSP) is proposed, with improved encoding and decoding and an optimized genetic evolution strategy. In addition, the problem of multi-objective optimization is solved by using non-dominated ordering and congestion computation. Experimental results show that the proposed method outperforms the MOEA/D algorithm in scheduling efficiency.