基于熵极大准则的非用户赋适应值交互式遗传算法OA北大核心CSCDCSTPCD
An Interactive Genetic Algorithms Based on Maximum Entropy Principle with Individuals' Fitness not Assigned by User
针对交互式遗传算法适应值人工赋值极易疲劳导致的算法进化代数不足、优化效率低下这一难题,提出了适应值非用户赋值方法.首先,用户对个体采用二元评价机制评价个体,将个体划分为满意集合和不满意集合;然后,根据个体评价时间与偏好的内在联系,通过个体评价时间确定评价满意度;最后,基于熵极大准则求解满意度最大条件下的个体适应值.为了确保优势基因遗传,加快算法收敛,采取种群精英基因构建优势个体保留策略.将该方法应用于装饰性墙壁纸选型系统中,并与其他代表性算法比较…查看全部>>
The fitness assigned by user can easily make fatigue which causes insufficient evolution algebra and low optimization efficiency for interactive genetic algorithms.In this study,a method of interactive genetic algorithms with individuals' fitness not assigned by user is presented.First,the individuals could be divided into satisfied sets and not satisfied sets;then,the individuals satisfaction is determined through evaluation time;finally,the fitness is calc…查看全部>>
郭广颂;陈良骥
郑州航空工业管理学院机电工程学院,河南郑州450046天津工业大学机械工程学院,天津300387
信息技术与安全科学
交互式遗传算法熵极大准则适应值非用户赋值
interactive genetic algorithmsmaximum entropy principlefitnessnot assigned by user
《电子学报》 2017 (12)
面向复杂薄壁件高速加工的CAM/CNC制造系统基础问题研究
2997-3004,8
国家自然科学基金(No.51275485)河南省科技攻关项目(No.172102210513)
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