A diversity-control-oriented genetic algorithm (DCGA): performance in function optimization
作者： H. Shimodaira
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摘要: In genetic algorithms, in order to attain the global optimum without getting stuck at a local optimum, an appropriate diversity of structures population needs be maintained. I have proposed new algorithm called DCGA (diversity control-oriented algorithm) this goal. DCGA, next generation are selected from merged parents and their offspring on basis particular selection probability maintain structures. The major feature is that distance between structure best performance used as primary criterion it applied probabilistic function produces larger for with distance. optimization examined by experiments benchmark problems. Within range my experiments, showed superior seems promising competitor previously algorithm.
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