Impact of individuals' fitness expressions on interactive genetic algorithms' performances

Authors:
Dun-Wei Gong;Jie Yuan
Affiliations:
School of Information and Electrical Engineering, China University of Mining and Technology, Xuzhou, China;School of Information and Electrical Engineering, China University of Mining and Technology, Xuzhou, China
Venue:
CCDC'09 Proceedings of the 21st annual international conference on Chinese control and decision conference
Year:
2009

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Abstract

Interactive genetic algorithms involve a user to evaluate an individual's fitness. So far, there have been many expressions of an individual's fitness, but no mature result of their influences on IGAs' performances has come out. We review 5 representative fitness expressions in this paper, i.e. precise fitness, discrete fitness, interval fitness, fuzzy fitness, as well as the fitness not directly assigned by the user. Establishing a RGB color evolutionary system to collect data and based on many statistical methods, we analyze the impact of the above fitness expressions on interactive genetic algorithms' performances in detail, and make a research on the user's satisfaction degree. The achievements in this paper provide a foundation for choosing an appropriate fitness expression in real-world applications.