Research on Capacity Planning of Cold Rolled Steel Production Line Based on the Modified Differential Evolution Algorithm

Z. Sui, Ziyang Yu
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Abstract

: The problem of steel cold rolling production capacity is an important issue in steel production. In this paper, mathematical modeling is carried out to meet the actual constraints of production process, inventory, flow balance, etc. And to determine the type and corresponding output of a certain product in each machine in every process in the production network, then obtain the inventory of each product between processes. The objectives of the model are to maximize unit capacity and minimize production switching costs. Differential evolution is a population-based evolutionary algorithm. It has the characteristics of recording the best solution during searching history and exchanging and sharing information within the population. That is, the optimization problem can be solved through the cooperation and competition among individuals within the population. In this paper, the differential evolution algorithm is modified for steel cold rolling production line capacity planning problem, the modified differential evolution algorithm comparing with other multi-objectives genetic algorithm. The results show that the proposed algorithm is superior to other standard genetic algorithm and can fast convergence, thus verified the feasibility and effectiveness of the algorithm.
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基于改进差分进化算法的冷轧钢生产线产能规划研究
钢材冷轧产能问题是钢铁生产中的一个重要问题。本文针对生产过程、库存、流量平衡等实际约束进行了数学建模。并确定生产网络中每道工序每台机器上某一产品的种类及相应的产量,从而得到工序间各产品的库存。该模型的目标是使单位产能最大化,使生产转换成本最小化。差分进化是一种基于种群的进化算法。它具有在搜索历史中记录最佳解决方案和在种群内交换和共享信息的特点。也就是说,优化问题可以通过群体内个体之间的合作与竞争来解决。本文针对冷轧生产线产能规划问题对差分进化算法进行了改进,并将改进的差分进化算法与其他多目标遗传算法进行了比较。结果表明,该算法优于其他标准遗传算法,且收敛速度快,从而验证了该算法的可行性和有效性。
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