敏捷车间单元动态调度的协同演化遗传算法  

Co-evolution genetic algorithm for unit dynamic scheduling of agile workshop

作　　者：孔令夷[1] 

机构地区：[1]西安邮电大学管理工程学院,西安710061

出　　处：《黑龙江大学自然科学学报》2014年第2期255-262,共8页Journal of Natural Science of Heilongjiang University

基　　金：国家自然科学基金资助项目(71102149);工信部通信软科学研究项目(2013R01-2);教育部人文社会科学研究项目(12YJC790084);陕西省教育厅专项科研计划资助项目(12JK0056);西安邮电大学青年教师科研基金资助项目(ZL2011-22)

摘　　要：针对敏捷车间的单元动态调度方案进行了设计与开发,构建基于多代理系统的敏捷车间单元动态调度框架。提出自上至下以及自下至上相结合的单元动态调度思想,建立融入模糊理论的单元动态调度综合满意度函数,运用演化博弈论,给出Agent的资源优选演化稳定策略解释。通过本协同演化遗传算法,求得面向多项工作任务的车间资源重组全局优化解,结合聚类分析法作出了敏捷车间单元动态调度的最满意决策。调度实例验证了算法的有效性及可行性。Unit dynamic scheduling framework of agile workshop was built based on multi-agent sys- tem, facing unit dynamic scheduling solution design and development of agile workshop. Dynamic sched- uling thought was proposed with combination of both up-bottom and bottom-up approaches. Then, with integration of fuzzy theory, comprehensive satisfaction degree function of unit dynamic scheduling was es- tablished. Evolutionary stable strategy of resources optimization was explained based on evolutionary game theory. By co-evolution genetic algorithm, overall optimization solution of workshop resources reorgani- zation was acquired for many jobs, and the most satisfied decision of unit dynamic scheduling in agile workshop was made with combination of clustering analysis method. Finally, scheduling example was pro- vided to prove validity and feasibility of the algorithm.

关 键 词：敏捷车间 动态调度 多代理系统 演化博弈 单元 协同演化遗传算法 

分 类 号：TH166[机械工程—机械制造及自动化] TP18[自动化与计算机技术—控制理论与控制工程]