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15th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'03)
Multi-Modal Function Optimization Problem for Evolutionary Algorithm
Sacramento, California, USA
November 03-November 05
ISBN: 0-7695-2038-3
ASCII Text
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Pan Hao, Yuan Jingling, Zhong Luo, "Multi-Modal Function Optimization Problem for Evolutionary Algorithm," Tools with Artificial Intelligence, IEEE International Conference on, pp. 157, 15th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'03), 2003.
 
 
BibTex
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@article{ 10.1109/TAI.2003.1250184,
author = {Pan Hao and Yuan Jingling and Zhong Luo},
title = {Multi-Modal Function Optimization Problem for Evolutionary Algorithm},
journal ={Tools with Artificial Intelligence, IEEE International Conference on},
volume = {0},
year = {2003},
issn = {1082-3409},
pages = {157},
doi = {http://doi.ieeecomputersociety.org/10.1109/TAI.2003.1250184},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Tools with Artificial Intelligence, IEEE International Conference on
TI - Multi-Modal Function Optimization Problem for Evolutionary Algorithm
SN - 1082-3409
SP
EP
A1 - Pan Hao,
A1 - Yuan Jingling,
A1 - Zhong Luo,
PY - 2003
KW - multi-modal function
KW - subspace search
KW - evolutionary algorithm
VL - 0
JA - Tools with Artificial Intelligence, IEEE International Conference on
ER -
 
Pan Hao, Wuhan Technology of University
Yuan Jingling, Wuhan Technology of University
Zhong Luo, Wuhan Technology of University
In this paper, a new algorithm for solving multimodal function optimization problems- two-level subspace evolutionary algorithm is proposed. In the first level, the improved GT algorithm is used to do global recombination search so that the whole population can be separated into several niches according to the position of solutions; then, in the second level, the niche evolutionary strategy is used for local search in the subspaces gotten in the first level till solutions of the problem are found. The new algorithm has been tested on some hard problems and some good results are obtained.
Index Terms:
multi-modal function, subspace search, evolutionary algorithm
Citation:
Pan Hao, Yuan Jingling, Zhong Luo, "Multi-Modal Function Optimization Problem for Evolutionary Algorithm," ictai, pp.157, 15th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'03), 2003
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