基于模糊聚类的冷轧合同组批优化方法

针对冷轧企业大批量生产模式与多品种、小批量的市场需求之间存在的矛盾, 建立以合同交货期差异度、工艺路线差异度和调整次数最小化为目标, 同时满足批次重量、出(入)口 宽度、出(入)口厚度、抗拉强度等工艺约束的冷轧合同组批模型, 构建了基于改进粒子群的模糊聚类算法并进行求解. 利用国内某冷轧企业实际生产数据对所提出模型和算法进行了验证, 结果表明, 所提出的方法优于FCM算法, 能够满足企业批量计划的需求.

Optimization method of order batching for cold rolling based on fuzzy clustering

Nowadays, one of the most important challenges faced by cold-rolling mills industries is the adjustment of the production mode in order to satisfy market requirements subjected to fluctuations over time, mainly product varieties, demands, etc. Therefore, an order batching model including three objectives is proposed, which are to minimize the difference of delivery, the difference of process route, and adjustment times of mills. Meanwhile, the model meets the requirements of process constraints such as the weight, the width of outlet(inlet), the thickness of outlet(inlet), and the tensile strength. And then a fuzzy clustering algorithm based on an improved particle swarm optimization which is used to solve the model is established. Experiments with real data of a cold-rolling mills production processes indicate that the proposed model and algorithm are superior to the FCM algorithm and can meet the requirement of the batch planning.