Summary
International Symposium on Nonlinear Theory and Its Applications
2015
Session Number:B4L-E
Session:
Number:B4L-E-4
Solution Search Performance of a Multi-Agent Solution Solving Method
Kenta Kohinata, Takuya Shindo, Kenya Jin'no,
pp.728-731
Publication Date:2015/12/1
Online ISSN:2188-5079
Summary:
In this article, we propose a novel deterministic multi-agent solution solving method that is based on the analysis result of our proposed canonical deterministic particle swarm optimization. The proposed method improves the local search ability by the controlling the search range. The proposed multi-agent solution solving method is similar to meta-heuristics. Comparing with other meta-heuristics, the solution search performance of the proposed multi-agent solution solving method is worse since the system is a deterministic system. However, the deterministic system is easy to implement because the system does not contain the stochastic factors. Thus, if the optimum solution search ability of the deterministic system is improved, the deterministic system is very useful. In this article, we propose the novel method to improve the solution search performance.