摘要
基于标准化适应值信息,提出改进的模糊交叉算子,并应用到细胞状遗传算法(CGA)中。在具有局部搜索倾向的交叉操作中,该算子能使后代更偏向于适应值高的父体。在具有全局搜索倾向的交叉操作中,能使较差个体在更大范围内进行搜索,有效地引导CGA算法向全局最优解的方向收敛。仿真实验结果表明,基于改进模糊交叉算子的CGA算法性能更好。
An advanced fuzzy recombination operator named SFFRO is proposed based on standardized fitness and applied to Cellular Genetic Algorithm（CGA）. The exploitative SFFRO has much more probability to generate offspring closer to the parent with higher fitness, and in the other hand, the explorative SFFRO tends to search in a larger scale for the parent with lower fitness. Therefore, SFFRO indicates the potential search direction and accelerates the convergence to global optimum. In the simulation research, experimental results show that CGA based on SFFRO obviously outperforms others in terms of efficiency and reliability.
出处
《计算机工程》
CAS
CSCD
北大核心
2008年第5期176-178,共3页
Computer Engineering
基金
国家自然科学基金资助项目(60573056)
福建省自然科学基金资助项目(A0710013)
福建省青年人才基金资助项目(2006F3085)
关键词
模糊交叉算子
多蜂分布
三角概率分布
细胞状遗传算法
fuzzy recombination operator
multimodal distribution
triangular probability distribution
cellular genetic algorithm
