基于遗传算法的作业车间提前/拖期调度问题

摘要

To deal with the Job Shop scheduling problem with due window hard rationing and earliness/tardiness parts punishment of jobs, a new Enhanced Genetic Algorithm （EGA） based on a two phase solution strategy was designed, which included converse push back and consequent pull over. Because some chromosomes disobeyed due window hard rationing in decoding process, illegal solutions were generated. Aiming at this problem, chromosome repair method based on critical path was used to adjust gene sequence of chromosome. Thereby, satisfaction of due window hard rationing as well as reduction of parts delay cost could be realized. Based on keeping tardiness costs unchanged, a target value revision method based on reverse rescheduling was put forward to postpone job release date to reduce flowtime costs and earliness costs introduced by each job. The proposed method was tested on a wide range of 80 scheduling problems. Results demonstrated its advantages in reducing total cost and tardiness cost.%针对带有交货期窗口硬约束并对提前/拖期零件进行惩罚的一类作业车间调度问题,设计了一种改进型遗传算法,该算法采用＂逆向后推＂和＂顺向前拉＂相结合的两阶段求解策略。针对部分染色体在解码过程中违反交货期窗口硬约束而产生非法解的问题,采用基于关键路径的染色体修复方法来调整染色体基因序列,以期实现在满足交货期窗口硬约束的同时降低零件拖期成本;在保持第一调度阶段拖期成本不变的基础上,采用基于逆向重调度的目标值修订方法来延迟零件开工时间,以降低在制品流动成本和成品提前库存成本。通过80组调度测试用例的仿真结果表明,该算法在降低调度总成本和拖期成本方面具有一定的优势。