DocumentCode
2033675
Title
An Exploring Coevolution Multi-Agent System for Multimodal Function Optimization
Author
Shi Xuhua ; Yu Haizhen
Author_Institution
Res. Inst. of Electr. Autom. Control, NingBo Univ., Ningbo
fYear
2009
fDate
23-24 May 2009
Firstpage
1
Lastpage
4
Abstract
Based on evolution theory and multi-agent cooperation mechanism, an Exploring Coevolution Multi-agent System (ECoEMAS) which aims at improving performance of multimodal optimization problems is proposed. Compared with other search methods, ECoEMAS is based on coevolution idea and several novel operations such as dynamic tasks allocation, asynchronous evolution, dynamic solutions memory and hill-valley exploring. These modifications are tested and showed successfully for both static and dynamic benchmarks. Comparative analysis illustrates ECoEMAS´s potential value.
Keywords
evolutionary computation; multi-agent systems; optimisation; exploring coevolution multi agent cooperation system; multimodal function optimization; Automatic control; Benchmark testing; Centralized control; Constraint optimization; Control systems; Electrostatic precipitators; Genetic algorithms; Multiagent systems; Partitioning algorithms; Search methods;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Systems and Applications, 2009. ISA 2009. International Workshop on
Conference_Location
Wuhan
Print_ISBN
978-1-4244-3893-8
Electronic_ISBN
978-1-4244-3894-5
Type
conf
DOI
10.1109/IWISA.2009.5072714
Filename
5072714
Link To Document