This research attempts to devise a multistage and multiproduct short-term integrative production plan that can dynamically change based on the order priority and virtual occupancy for application in steel plants. Considering factors such as the delivery time, varietal compatibility between different products, production capacity of variety per hour, minimum or maximum batch size, and transfer time, we propose an available production capacity network with varietal compatibility and virtual occupancy for enhancing production plan implementation and quick adjustment in the case of dynamic production changes. Here available means the remaining production capacity after virtual occupancy. To quickly build an available production capacity network and increase the speed of algorithm solving, constraint selection and cutting methods with order priority were used for model solving. Finally, the genetic algorithm improved with local search was used to optimize the proposed production plan and significantly reduce the order delay rate. The validity of the proposed model and algorithm was numerically verified by simulating actual production practices. The simulation results demonstrate that the model and improved algorithm result in an effective production plan.

本研究试图设计一种可根据订单优先级和虚拟占用率动态变化的多阶段、多产品短期综合生产计划，以应用于钢铁厂。考虑到交货时间、不同产品之间的品种兼容性、每小时品种的生产能力、最小或最大批量以及转移时间等因素，我们提出了一个具有品种兼容性和虚拟占用率的可用生产能力网络，以加强生产计划的实施和在动态生产变化的情况下快速调整。这里可用是指虚拟入住后的剩余产能。快速构建可用的产能网络，提高算法求解速度，模型求解采用约束选择和排序优先的切割方法。最后，采用局部搜索改进的遗传算法对提出的生产计划进行优化，显着降低订单延迟率。通过模拟实际生产实践，对所提出的模型和算法的有效性进行了数值验证。仿真结果表明，该模型和改进算法产生了一个有效的生产计划。