摘要
针对工件投料时间和机器起用时间不为零的柔性车间多目标优化调度问题,提出了一种改进遗传算法。染色体编码采用机器分配链和工序顺序链的双链结构;用均匀设计法、最短加工时间机器指配法、随机生成法三种方式产生初始种群;由锦标赛方法、最优保存策略和新生策略混合进行选择操作;以传统交叉方式、面向瓶颈机器的交叉方式,以及面向瓶颈工件的交叉方式混合进行交叉操作;以变动概率的方式进行变异操作;用启发式规则控制解码过程。最后,对典型算例进行了验证计算。研究结果表明该算法具有较强的寻优能力,并具有较快的求解速度。
For the multi-objective scheduling of the flexible job-shop problem with a non-zero part-arrive-time and machine-available-time,an improved genetic algorithm was proposed.Double-chain structure with machine-allocation-chain and operation-sequence-chain was used to code the chromosome;Population was initialized with three methods： uniform design,shortest-processing-time machine assignment,and random generation.Population selection was performed with tournament-selection,elitist-selection,and new-born-selection.A hybrid crossover method was proposed,including traditional crossover,machine-bottleneck oriented and job-bottleneck oriented crossover.The mutation was performed with an adaptable probability.The decoding process was controlled with heuristic rules.Finally,case-studies based on some typical benchmark-examples were carried out to evaluate the algorithm.The results show a quicker speed and powerful optimizing capability.
出处
《机电工程》
CAS
2011年第3期269-274,304,共7页
Journal of Mechanical & Electrical Engineering
基金
国家高技术研究发展计划("863"计划)资助项目(2009AA04Z146)
浙江省制造业信息化重大科技攻关资助项目(2008C11012)
关键词
柔性车间调度
遗传算法
多目标优化
均匀设计
flexible job-shop scheduling
genetic algorithm
multi-objective optimization
uniform design
