DocumentCode
2671693
Title
Parameter setting for knowledge evolution algorithm
Author
Xu Mengjun ; Ma Huimin
Author_Institution
Bus. Sch., Univ. of Shanghai for S & T, Shanghai, China
fYear
2012
fDate
23-25 May 2012
Firstpage
2409
Lastpage
2414
Abstract
Knowledge evolution algorithm (KEA) is a new optimization algorithm relies on the mechanism of knowledge evolution, and a series of parameters used in the algorithm play an important role in the optimization performance. Based on the knapsack problems, basic principles of parameter setting are proposed by using simulation experiments, which are beneficial to further application and promotion of the algorithm.
Keywords
artificial intelligence; knapsack problems; optimisation; knapsack problems; knowledge evolution algorithm; optimization algorithm; optimization performance; parameter setting principle; Aerospace electronics; Algorithm design and analysis; Business; Convergence; Educational institutions; Optimization; Standards; Knapsack Problem; Knowledge Evolution Algorithm; Optimization; Parameter Setting;
fLanguage
English
Publisher
ieee
Conference_Titel
Control and Decision Conference (CCDC), 2012 24th Chinese
Conference_Location
Taiyuan
Print_ISBN
978-1-4577-2073-4
Type
conf
DOI
10.1109/CCDC.2012.6244386
Filename
6244386
Link To Document