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Multi-objective scheduling of industrial intelligent manufacturing workshops based on variable neighbourhood genetic algorithm

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  • Junzhi Song

Abstract

Traditional multi-objective scheduling methods in industrial intelligent manufacturing workshops suffer from low efficiency and long scheduling minimisation time. To address this issue, a new multi-objective scheduling method of industrial intelligent manufacturing workshops based on variable neighbourhood genetic algorithm is designed. Industrial intelligent manufacturing workshop multi-objective parameters are selected, including completion time, completion process, machine load, and cost. A multi-objective scheduling function is built using the obtained parameters. The variable neighbourhood genetic algorithm is employed to generate neighbourhood sequences and initial solutions, and genetic operations such as encoding, mutation, and crossover are applied to form a new population, thereby achieving the solution of the objective function and realising optimal scheduling. The test results show that the algorithm proposed in this paper can improve the multi-objective scheduling efficiency of industrial intelligent manufacturing workshops and reduce the minimum scheduling time.

Suggested Citation

  • Junzhi Song, 2025. "Multi-objective scheduling of industrial intelligent manufacturing workshops based on variable neighbourhood genetic algorithm," International Journal of Manufacturing Technology and Management, Inderscience Enterprises Ltd, vol. 39(3/4/5), pages 300-318.
    • Handle: RePEc:ids:ijmtma:v:39:y:2025:i:3/4/5:p:300-318
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