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基于个体适应值灰模型的交互式遗传算法
引用本文:郭广颂,赵绍刚.基于个体适应值灰模型的交互式遗传算法[J].计算机工程,2010,36(3):209-212.
作者姓名:郭广颂  赵绍刚
作者单位:1. 郑州航空工业管理学院机电工程学院,郑州,450015
2. 徐州师范大学物理与电子工程学院,徐州,221116
基金项目:国家自然科学基金资助项目(60775044)
摘    要:为将交互式遗传算法应用于复杂的优化问题中,提出一种基于进化个体适应值灰模型预测的交互式遗传算法,为每代适应值序列建立灰模型,以衡量个体适应值评价的不确定性,通过对灰模型的灰预测,提取进化个体评价的可信度,在此基础上,给出进化个体适应值修正公式,将该算法应用于服装进化设计系统中。实验结果表明,该算法在每代都能获取更多的满意解。

关 键 词:遗传算法  交互  灰模型  适应值
修稿时间: 

Interactive Genetic Algorithm Based on Grey Model of Individual Fitness
GUO Guang-song,ZHAO Shao-gang.Interactive Genetic Algorithm Based on Grey Model of Individual Fitness[J].Computer Engineering,2010,36(3):209-212.
Authors:GUO Guang-song  ZHAO Shao-gang
Affiliation:(1. School of Mechatronics Engineering, Zhengzhou Institute of Aeronautical Industry Management, Zhengzhou 450015; 2. College of Physics and Electronic Engineering, Xuzhou Normal University, Xuzhou 221116)
Abstract:In order to apply the interactive Genetic Algorithm(GA) into complicated optimization problems, an Interactive GA(IGA) with grey modeling prediction for fitness of evolutionary individuals is proposed, in which the fitness uncertainty of evolutionary individuals is measured expressed by grey modeling. By predicting the grey modeling, the reliableness which reflects the measuring is abstracted. On this basis, the formulation of fitness adjustment is presented. The algorithm is applied to a fashion evolutionary design system, and experimental results show it can find more satisfactory solutions per generation.
Keywords:Genetic Algorithm(GA)  interaction  grey model  fitness
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