工期不确定的模具车间柔性Flow-shop调度问题

Scheduling of Flexible Flow Shop for Mold Manufacturing with Processing Time Uncertainty

由于模具制造属于非重复性单件订货生产,模具加工的任务工期具有较强的不确定性,导致生产调度混乱。为制定合理可行的生产调度方案,建立了任务工期离散概率模型,以最大完工时间的期望值最小为目标,建立不确定工期柔性Flow-shop调度模型;在遗传算法交叉、变异等操作中融入模拟退火操作,将遗传算法的全局搜索能力与模拟退火算法的良好局部搜索能力相结合,设计了不确定工期的柔性Flow-shop调度问题混合遗传模拟退火算法。利用混合遗传模拟退火算法对调度模型进行求解,通过仿真实验表明,该研究对于解决工期不确定的模具车间柔性Flow-shop调度问题是行之有效的。

Mold manufacturing is a non-repeated process,but it is of single order production.For such processes,part processing time uncertainty is the main characteristics.Thus,in mold manufacturing,the operation may enter a chaotic state due to bad scheduling.In order to obtain a reasonable and feasible production schedule under processing time uncertainty,a discrete probability model is developed for a flexible mold manufacturing flow shop.Then,a scheduling model is presented for minimizing the expectation of makespan.The problem is solved by a hybrid genetic algorithm which integrates simulated annealing algorithm into the crossover and mutation operations.The proposed method is tested by using practical cases and results show that it is effective.