基于改进遗传算法的热轧批量计划优化模型

针对钢铁企业的热轧批量计划编制问题,考虑了热轧生产工艺规程、同宽板坯连轧长度限制等约束,建立基于不确定旅行商数的多旅行商问题(MTSP)的热轧批量计划数学模型,把轧制单元计划数最小化和紧邻轧制板坯间轧制宽度、厚度、硬度差异而造成的总惩罚值最小化作为优化目标。结合模型的实际情况,采用基于两交换启发式的改进遗传算法对问题进行求解。最后,利用某钢厂的实际生产数据进行计算试验,同时对结合传统遗传算法和改进遗传算法的优化情况进行对比和结果分析,模型的正确性和算法的有效性得到了验证。

Optimization model of hot rolling batch planning based on improved genetic algorithm

Aiming at the hot rolling batch planning problem of iron and steel enterprises, considering the constraints of the hot rolling production process and the limitation of the same width slab rolling length, a mathematical model of hot rolling batch planning based on multiple traveling salesman problem (MTSP) with uncertain traveling salesman number was established, the optimization goal was to minimize the number of rolling unit plans and minimize the total penalty value caused by the difference of rolling width, thickness, and hardness between the adjacent rolled slabs. Combined with the actual situation of the model, an improved genetic algorithm based on two exchange heuristics was used to solve the problem. Finally, the actual production data of a steel plant was used to carry out the calculation experiments. At the same time, the optimization situation of the traditional genetic algorithm and the improved genetic algorithm was compared and the results were analyzed, this paper verifies the correctness of the model and the effectiveness of the algorithm were verified.