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Energy-Saving Production Scheduling in a Single-Machine Manufacturing System by Improved Particle Swarm Optimization

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  • Qingquan Jiang
  • Xiaoya Liao
  • Rui Zhang
  • Qiaozhen Lin

Abstract

A single-machine scheduling problem that minimizes the total weighted tardiness with energy consumption constraints in the actual production environment is studied in this paper. Based on the properties of the problem, an improved particle swarm optimization (PSO) algorithm embedded with a local search strategy (PSO-LS) is designed to solve this problem. To evaluate the algorithm, some computational experiments are carried out using PSO-LS, basic PSO, and a genetic algorithm (GA). Before the comparison experiment, the Taguchi method is used to select appropriate parameter values for these three algorithms since heuristic algorithms rely heavily on their parameters. The experimental results show that the improved PSO-LS algorithm has considerable advantages over the basic PSO and GA, especially for large-scale problems.

Suggested Citation

  • Qingquan Jiang & Xiaoya Liao & Rui Zhang & Qiaozhen Lin, 2020. "Energy-Saving Production Scheduling in a Single-Machine Manufacturing System by Improved Particle Swarm Optimization," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-16, November.
    • Handle: RePEc:hin:jnlmpe:8870917
    DOI: 10.1155/2020/8870917
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    Cited by:

    1. Adrian Kampa & Iwona Paprocka, 2021. "Analysis of Energy Efficient Scheduling of the Manufacturing Line with Finite Buffer Capacity and Machine Setup and Shutdown Times," Energies, MDPI, vol. 14(21), pages 1-25, November.

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