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Optimization of Rolling Schedule in Tandem Cold Mill Based on QPSO Algorithm

机译:基于QPSO算法的串联冷轧机中轧辊调度的优化

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This paper adopts equal relatively load as objective function, and makes every parameter to meet certain restrictive conditions. SUMT algorithm was used to change constraints to non-binding conditions. QPSO algorithm was applied to optimize objective functions to obtain optimal solution. This algorithm was based on classical particle swarm optimization, which, with the conduct of quantum particle, had effective global search capability, good convergence and stability. As a result, reasonable distribution of tandem cold rolling power and full use of equipment capacity were realized, resulting in the improvement of production efficiency.
机译:本文采用相对相对负载的目标函数,并使每个参数满足某些限制性条件。 SUMT算法用于将约束改变为非绑定条件。 QPSO算法应用于优化目标函数以获得最佳解决方案。该算法基于经典粒子群优化,随着量子粒子的进行,具有有效的全球搜索能力,良好的收敛性和稳定性。结果,实现了合理分布的串联冷轧动力和充分利用设备容量,导致生产效率的提高。

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