摘要
针对柔性作业车间调度问题,选取三个性能指标作为求解目标。将蚁群算法与模糊属性权重结合在一起,提出了求解FJSP的新算法。该算法利用了蚁群算法的正反馈机制,在逐步构造解的过程中利用最优解信息和启发式信息增强全局求解能力,寻求各目标较好的全局最优解。采用模糊属性权重对各目标进行综合评价,最终求解出FJSP问题的最优解集。
According to the characteristics of flexible job-shop scheduling problem, selecting three performance indexes as solving target, and combining ant colony algorithm with fuzzy attribute weight, it proposes a new algorithm to solve FJSP. This algorithm uses the positive feedback mechanism of ant colony algorithm, and takes advantage of optimal solution information and heuristic information to enhance global solving ability in process of gradual constructing solution, which is in order to seek better global optimal solution for each target. Then it applies fuzzy attribute weight to take comprehensive evaluation on each target which finally concludes the optimal solution set of FJSP.
出处
《微型机与应用》
2012年第9期72-74,共3页
Microcomputer & Its Applications
基金
兰州交通大学大学生科技创新项目(DXS2011-023)
兰州交通大学大学生创新性实验(201062)
关键词
柔性作业车间调度
蚁群算法
模糊属性权重
信息素更新规则
flexible job-shop scheduling problems
ant colony algorithm
fuzzy attribute weight
pheromone updating rule
