平顺移动下等量分批FJSP多目标优化研究

为解决平顺移动下等量分批柔性作业车间调度问题多目标优化的困难,对平顺移动下等量分批柔性作业车间调度多目标优化方法进行了深入研究。首先,针对平顺移动方式下等量分批柔性作业车间调度的特点,建立了一类以完工时间最短和制造成本最低为优化目标的等量分批柔性作业车间调度多目标优化模型。其次,提出并设计了一种改进的NSGA II算法对模型进行求解。算法中引入面向对象技术处理复杂的实体逻辑关系,使用一种基于工序及设备编码的分段编码技术进行编码,采用分段交叉和变异的特殊遗传算子实现遗传进化,应用4种精细化调度技术于解码过程以提高设备利用率。最后,通过案例分析验证了方法的有效性。

Research on Multi-objective Optimization for Equal Batch Splitting FJSP under Parallel and Sequence Shift Mode

To resolve the difficulty of multi-objective optimization for equal batch splitting flexible job-shop scheduling problem(FJSP) under parallel and sequence shift mode,a multi-objective optimization method for equal batch splitting FJSP under parallel and sequence shift mode was studied deeply.Firstly,aiming at the characteristic of equal batch splitting FJSP under parallel and sequence shift mode,a multi-objective optimization model was established with the objective to minimize the makespan and the manufacturing cost.Then,an improved NSGA II algorithm was presented and designed to resolve the model.In the algorithm,a technique of object oriented was introduced to deal with the complicated logical relation between different entities,a segmented coding technique based on processes and machines was used to code the processing sequence and machines,a special segmented crossover and mutation operator was used to implement genetic evolution,four delicacy scheduling techniques were applied to improve the utilization ratio of machines during the decoding process.Finally,the effectiveness of the proposed research was validated by case study.