并行机作业车间等量分批多目标优化调度

摘要

To reduce the complexity and improve the solution efficiency of the equal lot scheduling problem of Job Shop with parallel machines, a stepwise optimization method based on simulation technology and improved Nondominated Sorting Genetic Ⅱ (NSGA Ⅱ ) algorithm was proposed.A multi-objective optimization model for the equal lot scheduling problem of Job Shop with parallel machines was constructed with the objectives to minimize the makespan and manufacturing cost.The production task of each product was divided into sub-tasks with equal lot.Taking Witness as the simulation platform, a production simulation model based on the equal lot scheduling of Job Shop with parallel machines was established.Based on the model, the ideal batching scheme was obtained through the combinatorial simulation optimization.Thus, the original scheduling problem was transformed to a multi-objective optimization scheduling problem for Job Shop with parallel machines.An improved NAGA Ⅱ algorithm was designed to resolve the multi-objective optimization scheduling problem for Job Shop with parallel machines.The effectiveness of the scheduling method proposed was validated by case study.%为降低并行机作业车间等量分批多目标优化调度问题的复杂度,提高优化效率,提出了一种基于仿真技术和改进非支配排序遗传算法的分步优化方法.建立了一类以完工时间最短和总制造成本最低为优化目标的并行机作业车间等量分批多目标优化调度模型;将各产品进行等量分批,以Witness为仿真平台建立并行机作业车间等量分批生产仿真模型,通过组合仿真优化得到产品理想的等量分批方案,从而将原问题转化为并行机作业车间多目标优化调度问题;设计了一种改进的非支配排序遗传算法,对并行机作业车间多目标优化调度进行求解.通过算例分析验证了该方法的有效性.