考虑交货因素的热轧无缝钢管订单排程模型与算法

无缝钢管的市场需求具有多品种、小批量的特点，为了在满足客户需求的同时保证高效连续化生产，文章在满足生产工艺特征的基础上将配送地址和交货期等合同因素引入热轧无缝钢管订单排程问题中，建立了以适期交货、订单集中生产配送和最小化机器设备调整为优化目标的订单排程优化模型，并设计了两阶段求解算法：首先，以订单交货期与配送地址差异最小为目标，基于凝聚策略设计了订单聚类算法，将具有相同工艺约束、相似合同要求的订单进行聚类，并形成初始轧制计划；然后，以设备调整和提前/拖期最小为目标，设计混合变邻域搜索算法，对初始轧制批次进行排程优化。基于实际订单数据的实验结果表明，模型和算法对问题的描述和求解是可行有效的。

Order Scheduling Model and Algorithm for Hot-Rolled Seamless Steel Tube with Delivery Requirements

The market demand for hot-rolled seamless steel tube presents multi-variety and small-batch characteristics, and delivery addresses and delivery time of orders are usually different. In this paper, the problem of hot-rolled order scheduling of seamless steel tube is extracted and defined from actual production. Hot-rolled order scheduling is the process of combining production orders into rolling batches and scheduling rolling batches sequence. In order to meet customer needs and ensure production efficiency and continuity, delivery factors, such as delivery address and delivery time, are introduced to the order scheduling. Moreover, considering delivery requirements and process characteristics, a model for this order scheduling problem is built to optimize the delivery period, ensure concentrated production and distribution, and minimize the total setup time of machines. A two-stage algorithm is provided further. In the first stage, to minimize differences among delivery time and addresses of orders, a hierarchical clustering algorithm is put forward on cohesion policy to cluster orders with the same process constraints and similar delivery requirements, thereby forming an initial rolling plan. In the second stage, a hybrid variable neighborhood search algorithm is presented to improve the initial plan in terms of setup times and earlyness/tardiness. Results of experiments with actual order data show the effectiveness of the model and algorithm. This research has a useful reference for the study of order scheduling problem of other steel products or products involving complex process and delivery constraints.