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Reference-point-based GWO algorithm for cutting parallel scheduling problems with bi-criteria objective

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Listed:
  • Ronghua Meng
  • Yunqing Rao
  • Zhengjia Wu
  • Xiaofei Xu

Abstract

This study investigates an unrelated parallel machine scheduling problem (UPMSP) with machine eligibility, setup times, and collecting times, which is inspired from a realistic scheduling problem in the cutting workshop. A new mixed-integer programming model that minimises total cost and makespan is proposed to address this problem. The main characteristic of UPMSP is the available machine constraint. An improved grey wolf optimiser (GWO) with non-dominated sorting and reference-point-based selection strategy balance the distribution of the Pareto solutions. The improved encircling and attacking strategies help to avoid the local optima or adjust the evolutionary direction. The proposed algorithm is compared with four other algorithms in our paper. Experimental results demonstrate that the proposed algorithm outperforms the other algorithms, especially in terms of the number and distribution of Pareto solutions. [Submitted: 26 July 2019; Accepted: 24 March 2021]

Suggested Citation

  • Ronghua Meng & Yunqing Rao & Zhengjia Wu & Xiaofei Xu, 2026. "Reference-point-based GWO algorithm for cutting parallel scheduling problems with bi-criteria objective," European Journal of Industrial Engineering, Inderscience Enterprises Ltd, vol. 22(1), pages 1-21.
    • Handle: RePEc:ids:eujine:v:22:y:2026:i:1:p:1-21
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