Game-based hybrid particle swarm optimization of job-shop production control

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Abstract

The traditional multi-objective particle swarm optimization (PSO) cannot effectively handle the production control problem involving multiple types of production lines or production objectives. Therefore, this paper designs a game-based hybrid PSO (GBHPSO) for job-shop production control. Firstly, a job-shop model was established with parts processing line, parts assembly line, and product assembly line, and the production control ideas were designed to combine real-time monitoring of events and operation sequence adjustment. Then, the production control objectives were determined for the three production lines. After that, the GBHPSO was applied to solve the job-shop production control problem, the product utility function was constructed, and the execution low was detailed for the solving algorithm. Experiments demonstrate the effectiveness of our algorithm. The research provides a reference for applying our algorithm in resource allocation of other production fields.

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APA

Wang, X. L. (2021). Game-based hybrid particle swarm optimization of job-shop production control. International Journal of Simulation Modelling, 20(2), 398–409. https://doi.org/10.2507/IJSIMM20-2-CO9

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