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

Authors: Junzhi Song

Addresses: Southwest Jiaotong University Hope College, Cheng'du, 610400, China; Chengdu Transportation + Tourism Big Data Application Technology Research, Cheng'du, 610400, China

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.

Keywords: intelligent manufacturing workshop; variable neighbourhood genetic algorithm; multi-objective scheduling; parameters; objective function.

DOI: 10.1504/IJMTM.2025.145943

International Journal of Manufacturing Technology and Management, 2025 Vol.39 No.3/4/5, pp.300 - 318

Received: 08 Jan 2024
Accepted: 03 Jun 2024
Published online: 30 Apr 2025 *

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