A Novel Evolutionary Algorithm with Improved Genetic Operator and Crossover Strategy

被引：1
|
作者：
Yao Huanmin [1 ]
Cai Mingdi [1 ]
Wang Jiekai [1 ]
Hu Ruikai [1 ]
Liang Yu [1 ]
机构：
[1] Harbin Normal Univ, Coll Math Sci, Harbin, Heilongjiang Pr, Peoples R China
来源：
INFORMATION TECHNOLOGY APPLICATIONS IN INDUSTRY II, PTS 1-4 | 2013年 / 411-414卷
关键词：
Evolutionary Algorithm; Population Initialization; Crossover Operator; Mutation Operator; Crossover Strategy; Schema Theorem;
D O I：
10.4028/www.scientific.net/AMM.411-414.1956
中图分类号：
TH [机械、仪表工业];
学科分类号：
0802 ;
摘要：
An improved evolutionary algorithm (SCAGA) is proposed in this paper. The algorithm is based on new population initialization method and genetic operator. SCAGA adopts the crossover probability and mutation probability that vary with the increase of evolution generation in order to control genetic operations in an effective range. Meanwhile, SCAGA presents a new crossover strategy that restricts the cross of the chromosomes to some extent to protect good genes schema. The schema theorem is employed in the algorithm to analyze the working mechanism of SCAGA. According to experiment results for test functions and TSP problems, SCAGA is effective.
引用
收藏
页码：1956 / 1965
页数：10
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