National Natural Science Foundation of China (No.51275485);Science and Technology Research and Development Program of Heinan Province (No.172102210513)
GUO Guang-song, CHEN Liang-ji. An Interactive Genetic Algorithms Based on Maximum Entropy Principle with Individuals' Fitness not Assigned by User[J]. Acta Electronica Sinica, 2017, 45(12): 2997-3004.
DOI:
GUO Guang-song, CHEN Liang-ji. An Interactive Genetic Algorithms Based on Maximum Entropy Principle with Individuals' Fitness not Assigned by User[J]. Acta Electronica Sinica, 2017, 45(12): 2997-3004. DOI: 10.3969/j.issn.0372-2112.2017.12.023.
An Interactive Genetic Algorithms Based on Maximum Entropy Principle with Individuals' Fitness not Assigned by User
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.