多目标等量分批柔性作业车间调度集成优化方法

摘要

Aiming at the multi-objective optimization problem for the equal lot splitting flexible job-shop scheduling, an integrated optimization method is proposed. Firstly, a multi-objective optimization model is established with the objective to minimize the makespan and minimize the manufacturing cost. Then, an improved Non-dominated Sorting Genetic Algorithm II (NSGA II) is presented and designed to solve the model. In the algorithm, an object-oriented technique is introduced to deal with the complicated logical relation between different entities, a three-segment encoding technique is used to encode the lot splitting scheme, the process sequences and machines, a three-segment hybrid crossover and mutation operator is used to implement genetic evolution, and two delicacy scheduling techniques are applied to reduce the flow time of each sub-batch. Finally, the effectiveness of the scheduling method proposed is validated by case study.%针对多目标等量分批柔性作业车间调度问题,提出了一种集成优化方法.构建了一种以完工时间最短、生产成本最低为优化目标的多目标等量分批柔性调度集成优化模型.提出并设计了一种改进的非支配排序遗传算法对模型加以求解.算法中引入面向对象技术处理复杂的实体逻辑关系,采用三段式分段编码技术分别对分批方案、加工顺序、设备进行编码,采用三段式分段交叉和变异的混合遗传算子实现遗传进化,采用两种精细化调度技术进行解码以缩短流程时间.通过案例分析验证了所提方法的有效性.