基于遗传算法的钢板罩退工序生产调度优化

Scheduling Problem of Sheet Plant’s bell annealing Based on Genetic Algorithms

针对钢铁薄板生产瓶颈工序,建立基于设备约束、产品约束、时间约束和批次约束数学模型,通过遗传算法寻优计算,得到较优可行解。结果显示,工序订单完成时间较实际生产时间减少,并且随着订单规模的增加,优化效果更加明显,但达到一定程度后趋于稳定。研究结果为薄板生产中罩退工序的调度问题优化提供了新思路、新方法,能够帮助企业有效提升生产效率和经济效益。

Aiming at the bottleneck process of steel sheet production, a mathematical model based on equipment constraints, product constraints, time constraints and batch constraints was established, through genetic algorithm optimization calculation, the better feasible solution is obtained. The results show that the weighted completion time is better than the corresponding actual production scheduling results, and with the increase of the scale of the problem, the superiority is more obvious. The research results provide a new idea and method for the scheduling optimization of the bell annealing process of Sheet Plant, which can help enterprises effectively improve production efficiency and economic benefits.