Akademik Veri Yönetim Sistemi
10th International Conference on Parallel Problem Solving from Nature, Dortmund, Almanya, 13 - 17 Eylül 2008, cilt.5199, ss.559-561
Noisy fitness function occur in many practical applications of evolutionary computation. A standard technique for solving these problems is fitness resampling but this may be inefficient or need a large population, and combined with elitism it may overvalue chromosomes or reduce, genetic diversity. We describe a simple new resampling technique called Greedy Average Sampling for stedy-state genetic algorithms such as GENITOR. It requires an extra runtime parameter to be tuned, but does not need a large population or assumptions on noise distributions. In experiments on a well-known Inventory Control problem it, performed a large number of samples on the best chromosomes yet only a small number average. and was more effective than four other tested techniques.