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
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;
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
DOI :
10.1109/IWISA.2009.5072714
