An Interactive Genetic Algorithms Based on Maximum Entropy Principle with Individuals' Fitness not Assigned by User
GUO Guang-song1, CHEN Liang-ji2
1. School of Mechatronics Engineering, Zhengzhou University of Aeronautics, Zhengzhou, Henan 450046, China;
2. School of Mechanical Engineering, Tianjin Polytechnic University, Tianjin 300387, China
Abstract：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 calculated based on the maximum entropy principle under the biggest satisfaction.In order to ensure protogene inheritance,the reserved elite individual is built by population elite genes.This method is applied to selection system of decorative wallpaper,and the results show that it can effectively reduce fatigue and improve the optimization efficiency.
郭广颂, 陈良骥. 基于熵极大准则的非用户赋适应值交互式遗传算法[J]. 电子学报, 2017, 45(12): 2997-3004.
GUO Guang-song, CHEN Liang-ji. An Interactive Genetic Algorithms Based on Maximum Entropy Principle with Individuals' Fitness not Assigned by User. Acta Electronica Sinica, 2017, 45(12): 2997-3004.
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2017, Vol. 45 
