Paper Info
Title
CSA/IE: novel clonal selection algorithm with information exchange for high dimensional global optimization problems
Abstract
In order to increase the diversity of immune algorithm when solving high dimensional global optimization problems, a novel clonal selection algorithm with information exchange (CSA/IE) is proposed. The main characteristics of CSA/IE are clonal expansion and a novel hypermutation strategy. In addition, a simplex crossover operator is introduced to improve the ability of information exchange. Particularly, a novel performance evaluation criterion is constructed in this paper, by which the performance of different population-based algorithms can be compared easily. The experimental results indicate that CSA/IE outperforms that of the conventional clonal selection algorithms and the three DE variants, in terms of the performance evaluation criterion proposed. Finally, the proposed CSA/IE is generalized to optimize some hyper-high dimensional (such as 100~1000 dimensions) unimodal and multimodal test functions, and the results show that the proposed algorithm performs well in terms of the stability and the solution quality.
Year
DOI
Venue
2012
10.1007/978-3-642-33757-4_17
ICARIS
Keywords
Field
DocType
clonal expansion,novel clonal selection algorithm,immune algorithm,different population-based algorithm,proposed csa,high dimensional global optimization,novel performance evaluation criterion,information exchange,novel hypermutation strategy,proposed algorithm,conventional clonal selection algorithm
Population,Artificial immune system,Mathematical optimization,Crossover,Computer science,Information exchange,Simplex,Artificial intelligence,Operator (computer programming),Clonal selection algorithm,Clonal selection,Machine learning
Conference
Citations 
PageRank 
References 
0
0.34
17
Authors
3
Name
Order
Citations
PageRank
Zixing Cai1152566.96
Xingbao Liu251.81
Xiaoping Ren393.19