DocumentCode :
2324759
Title :
Alternative hyper-heuristic strategies for multi-method global optimization
Author :
Grobler, Jacomine ; Engelbrecht, Andries P. ; Kendall, Graham ; Yadavalli, V.S.S.
Author_Institution :
Dept. of Ind. & Syst. Eng., Univ. of Pretoria, Pretoria, South Africa
fYear :
2010
fDate :
18-23 July 2010
Firstpage :
1
Lastpage :
8
Abstract :
The purpose of this paper is to investigate the use of meta-heuristics as low-level heuristics in a hyper-heuristic framework. A novel multi-method hyper-heuristic algorithm which makes use of a number of common meta-heuristics is presented. Algorithm performance is evaluated on a diverse set of real parameter benchmark problems and meaningful conclusions are drawn with respect to the selection of alternative low-level heuristics and the acceptance of the obtained solutions within the proposed multi-method meta-heuristic approach.
Keywords :
heuristic programming; optimisation; alternative low-level heuristics; common metaheuristics; multimethod global optimization; multimethod hyper-heuristic algorithm; Algorithm design and analysis; Benchmark testing; Equations; Evolutionary computation; Heuristic algorithms; Optimization; Software algorithms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation (CEC), 2010 IEEE Congress on
Conference_Location :
Barcelona
Print_ISBN :
978-1-4244-6909-3
Type :
conf
DOI :
10.1109/CEC.2010.5585980
Filename :
5585980
Link To Document :
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