钢铁生产系统中成本最小化和工作量平衡的多工序物流规划

Zhuohan Zhang, Ziyan Zhao, Yang Zhang, Shixin Liu
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引用次数: 0

摘要

物流规划是钢铁生产系统中多工序协调的关键。本文研究了炼钢-热轧-冷轧过程中出现的一个新的、实用的双目标物流规划问题。它的首要目标是使固定成本、运输成本、缺货惩罚和库存成本的总和最小化。第二个是平衡并行机器的工作负载。针对这一问题,提出了一个混合整数线性规划。为了解决这个问题,遗传算法是专门为这个问题设计的。该方法首先通过对两个目标函数进行加权,将双目标优化问题转化为单目标优化问题。然后,通过调整加权系数得到Pareto解。实验结果与用CPLEX求解混合整数线性规划的结果进行了比较。验证了该方法的优良性能,表明了其在实际应用中的可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multi-Process Logistics Planning for Cost Minimization and Workload Balance in Steel Production Systems
Logistics planning is a key to the coordination of multiple processes in steel production systems. This work investigates a new and practical bi-objective logistics planning problem arising from steelmaking-hot rolling-cold rolling processes. Its first objective is to minimize the sum of fixed costs, transportation costs, out-of-stock penalties, and inventory costs. The second one is to balance the workload of parallel machines. A mixed integer linear program is formulated for the concerned problem. To solve it, a genetic algorithm is problem-specifically designed. In it, the concerned bi-objective optimization problem is first transformed into a single-objective one by weighting two objective functions. Then, Pareto solutions are obtained through the presented algorithm by adjusting the weighted coefficients. Experimental results obtained by the presented algorithm are compared with those obtained by solving the mixed integer linear program with CPLEX. Its great performance is verified, thus showing its readiness to be applied in practice.
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