“一刀切”排样问题的遗传算法与蚁群算法整合研究  

Research on the Itegration of Genetic Algorithm and Ant Colony Algorithm Applied in Guillotine Layout Problem

作　　者：李伟[1] 刘倩[1] 肖美丹[2] 

机构地区：[1]河北工业大学经济管理学院,天津300401 [2]河南农业大学信息与管理科学学院,河南郑州450002

出　　处：《成组技术与生产现代化》2013年第1期39-44,共6页Group Technology & Production Modernization

基　　金：河南省自然科学基金资助项目(12A630020)

摘　　要：对于"一刀切"矩形件优化排样问题,采用遗传算法与蚁群算法的混合算法进行研究.针对两种算法的传统混合策略和现有混合策略的不足,对两种算法的混合策略进行改进,并利用种群本身的染色体适值来判断种群进化是否停滞,确定了算法的最佳融合时机.对具体算例的分析验证表明,改进后的混合策略可有效减少算法的冗余迭代次数,提高搜索速度,是一种行之有效的排样算法.This research attemps to use hybrid algo- rithm which integrates the genetic algorithm and the ant colony algorithm to solve the guillotine rectangular optimal layout problem. There are shortcomings in the traditional mixed strategy and the current mixed strategy for the two algorithms. In order to overcome these shortcomings, this research improves the mixed strategy. Whether the evolu- tion of population is stagnant can be confirmed by the fit- ness of the population＇s chromosome. Best algorithm fusion time is determined through the research. It is verified by example analysis that the improved hybrid strategy can ef- fectively reduce algorithm redundancy iterations and improve search speed. The result shows that this algorithm is effec- tive.

关 键 词：“一刀切” 矩形件优化排样 遗传算法 蚁群算法 算法融合 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]