| An Effective Way to Neighborhood Construction for MAGA |
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| Xiaoying Pan,Licheng Jiao. An Effective Way to Neighborhood Construction for MAGA. International Journal of Software and Informatics, 2010,4(3):325~346 |
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| Fund:This work is sponsored by the Natural Science Project supported by Shaanxi Province Office ofEducation under Grant 112w017, the China Intelligent Transportation Technology Research Fundunder Grant 103-0335, the Natural Science Foundation of Xi’an Institute of Posts and Telecommunications under Grant 103-0402. |
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| Abstract:The MAGA is an effective algorithm used for global numerical optimization
problems. Drawbacks, however, still existed in the neighborhood selection part of the algorithm.
Based on the social cooperate mechanism of agents, an effective neighborhood
construction mode is proposed. This mode imports an acquaintance net which describes
the relation of agents, and uses that to construct the local environment (neighborhood)
for agents. This strategy makes the new mode more reasonable than that of MAGA. The
Multi-Agent Social Evolutionary Algorithm (MASEA) based on this construction mode is
introduced, and some standard testing functions are tested. In the first experiments, two
dimensional, 30 dimensional and 20-1000 dimensional functions are tested to prove the effectiveness
of this algorithm. The experimental results show MASEA can find optimal or
close-to-optimal solutions at a low computational cost, and its solution quality is quite stable.
In addition, the comparative results indicate that MASEA performs much better than
the CMA-ES and MAGA in both quality of solution and computational complexity. Even
when the dimensions reach 10,000, the performance of MASEA is still good. |
| keywords:multi-agent system evolutionary algorithm acquaintance net |
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