DocumentCode :
2982375
Title :
Fast evolutionary programming through search momentum and multiple offspring strategy
Author :
Cho, Hyeon-Joong ; Oh, Se-young ; Choi, Doo-Hyun
Author_Institution :
Dept. of Electr. Eng., Pohang Inst. of Sci. & Technol., South Korea
fYear :
1998
fDate :
4-9 May 1998
Firstpage :
805
Lastpage :
809
Abstract :
A new algorithm that helps to accelerate convergence as well as to enhance the diversity of the evolutionary programming (EP) search technique is proposed, based on an individual structure concept. The major components of the algorithm that lie behind its good performance includes scaling, selection strategy, the use of age and the search direction (or momentum) vector, and multiple offspring per parent. Not only are the multiple offspring approach and the search direction vector concept novel but the combination of these features used for EP is also new. Through a benchmark test, its search performance has been found to be superior to the conventional EP and one of its acceleration methods
Keywords :
convergence; genetic algorithms; programming; search problems; software performance evaluation; vectors; age; algorithm performance; benchmark test; convergence acceleration; diversity; fast evolutionary programming; individual structure concept; multiple offspring strategy; scaling; search direction vector; search momentum; search performance; selection strategy; Acceleration; Benchmark testing; Convergence; Cost function; Gaussian noise; Genetic algorithms; Genetic mutations; Genetic programming; Life estimation; Noise robustness;
fLanguage :
English
Publisher :
ieee
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
Type :
conf
DOI :
10.1109/ICEC.1998.700155
Filename :
700155
Link To Document :
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