Title :
The compact genetic algorithm
Author :
Harik, Georges R. ; Lobo, Fernando G. ; Goldberg, David E.
Author_Institution :
Silicon Graphics Comput. Syst., Mountain View, CA, USA
Abstract :
This paper introduces the “compact genetic algorithm” (cGA). The cGA represents the population as a probability distribution over the set of solutions, and is operationally equivalent to the order-one behavior of the simple GA with uniform crossover. It processes each gene independently and requires less memory than the simple GA
Keywords :
genetic algorithms; probability; compact genetic algorithm; independent gene processing; memory requirement; order-one behavior; population representation; probability distribution; solution set; uniform crossover; Algorithm design and analysis; Computer simulation; Evolutionary computation; Genetic algorithms; Genetic engineering; Graphics; Helium; History; Mathematical model; Probability distribution;
Conference_Titel :
Evolutionary Computation Proceedings, 1998. IEEE World Congress on Computational Intelligence., The 1998 IEEE International Conference on
Conference_Location :
Anchorage, AK
Print_ISBN :
0-7803-4869-9
DOI :
10.1109/ICEC.1998.700083
