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针对考虑柔性检修计划的圆钢热轧批量调度问题,构建了以最小化最大完工时间、订单提前及拖期总时长为目标函数的整数规划模型,用以制定有效的机器检修与批量生产协作计划。结合模型特征,提出一种改进多目标粒子群算法(IMPSO)实现求解。算法采用基于混沌加权适应度计算的插入式方法生成初始粒子群体;根据问题约束特征,设计修复规则对群体进化过程中产生的不可行粒子进行修复;采用精英策略保留算法迭代过程中的优势个体,并根据精英集合为每个粒子选择更新所需的极值;针对问题变量的离散特征,引入基于遗传操作的粒子更新方式。实验结果表明,模型和算法是可行和有效的。
In order to solve the batch scheduling problem of round bar hot rolling considering the flexible maintenance schedule, an integer programming model with the objective of minimizing the maximum completion time, order advancement and total tardiness as objective function is constructed to formulate an effective collaborative maintenance and mass production plan . Combined with the characteristics of the model, an improved multi-objective particle swarm optimization (IMPSO) is proposed to solve the problem. In this algorithm, an initial population of particles is generated by using a plug-in method based on chaos-weighted fitness calculation. According to the problem-constrained features, a repair rule is designed to repair the infeasible particles generated during the evolution of the population. Using the elitist strategy to retain the dominant individuals in the process of iteration, According to the discrete features of the problem variables, a particle updating method based on genetic operators is introduced. Experimental results show that the model and algorithm are feasible and effective.