Paper Info
Title
A Novel Genetic Algorithm Based on Multi-Agent Systems
Abstract
A new algorithm, Multi-Agent Genetic Algorithm (MAGA), is proposed for solving global numerical optimization problems. All agents live in a lattice-like environment, with each agent fixed on a lattice-point. In order to increase energies, they compete or cooperate with their neighbors, and they can also use knowledge. Theoretical analyses show that MAGA converges to the global optimum. In the experiments, 6 benchmark functions are used to test the performance of MAGA, and the scalability of MAGA along the problem dimension is studied with great care. The results show that MAGA achieves a good performance when the dimensions are increased from 20 to 10,000. Moreover, even when the dimensions are increased to as high as 10,000, MAGA still can find high quality solutions at a low computational cost.
Year
DOI
Venue
2004
10.1007/978-3-540-39985-8_18
INTELLIGENT INFORMATION PROCESSING AND WEB MINING
Keywords
Field
DocType
multi agent system,genetic algorithm
Data mining,Mathematical optimization,Computer science,Meta-optimization,Global optimum,Multi-agent system,Optimization problem,Genetic algorithm,Mutation operator,Scalability
Conference
ISSN
Citations 
PageRank 
1615-3871
0
0.34
References 
Authors
7
3
Name
Order
Citations
PageRank
Weicai Zhong138126.14
Jing Liu21043115.54
Licheng Jiao35698475.84