DocumentCode
1844791
Title
An Improved Genetic Algorithm Based on Variable Step-Size Search
Author
Zhu, Guannan ; Xu, Ning ; An, Zhulin ; Xu, Yongjun
Author_Institution
Wuhan Univ. of Technol., Wuhan
fYear
2008
fDate
18-21 Nov. 2008
Firstpage
1813
Lastpage
1818
Abstract
Genetic algorithms (GAs) are global optimization algorithms which can be used to solve different kinds of problems. However, in the situation that the size of feasible solution space is far less than that of search space, GAs may degrade to random searches. This paper presents an improved genetic algorithm, which adopts variable step-size algorithm to obtain a feasible solution, and reduce search space during the same process. The theoretical analysis and experiments in comparison with the random search are also presented,which indicate that this improved algorithm would reduce the search time in solving problems that have a large search space.
Keywords
genetic algorithms; search problems; global optimization algorithms; improved genetic algorithm; search space; variable step-size search; Algorithm design and analysis; Binary codes; Biological cells; Computers; Degradation; Genetic algorithms; Genetic mutations; Machine learning algorithms; Signal processing algorithms; Space technology; Genetic algorithms; search space reduction; variable step-size;
fLanguage
English
Publisher
ieee
Conference_Titel
Young Computer Scientists, 2008. ICYCS 2008. The 9th International Conference for
Conference_Location
Hunan
Print_ISBN
978-0-7695-3398-8
Electronic_ISBN
978-0-7695-3398-8
Type
conf
DOI
10.1109/ICYCS.2008.351
Filename
4709249
Link To Document