DocumentCode :
2563197
Title :
A Novel Hybrid Real-Valued Genetic Algorithm for Optimization Problems
Author :
Li, Hong-qi ; Li, Li
fYear :
2007
fDate :
15-19 Dec. 2007
Firstpage :
91
Lastpage :
95
Abstract :
Since genetic algorithm lacks hill-climbing capacity, it easily falls in a trap and finds a local minimum not the true solution. In this paper, a novel hybrid real- valued genetic algorithm (NHRVGA) combined with harmony search that merits of genetic algorithm and harmony search (HS) is proposed. It provides a new architecture of hybrid algorithms, which organically merges the harmony search (HS) method into real- valued genetic algorithm (RVGA). During the course of evolvement, harmony search is used to improve the search performance and this makes NHRVGA algorithm have more powerful exploitation capabilities. Simulation and comparisons based on several well- studied benchmarks demonstrate the effectiveness, efficiency and robustness of the proposed NHRVGA.
Keywords :
Biological cells; Biological information theory; Cities and towns; Computational intelligence; Computational modeling; Computer science; Computer security; Genetic algorithms; Petroleum; Stochastic processes;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence and Security, 2007 International Conference on
Conference_Location :
Harbin
Print_ISBN :
0-7695-3072-9
Electronic_ISBN :
978-0-7695-3072-7
Type :
conf
DOI :
10.1109/CIS.2007.158
Filename :
4415308
Link To Document :
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