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A Multi-Layered Immune System for Graph Planarization Problem Shangce GAO Rong-Long WANG Hiroki TAMURA Zheng TANG Publication IEICE TRANSACTIONS on Information and Systems Vol.E92-D No.12 pp.2498-2507 Publication Date: 2009/12/01 Online ISSN: 1745-1361 DOI: 10.1587/transinf.E92.D.2498 Print ISSN: 0916-8532 Type of Manuscript: PAPER Category: Biocybernetics, Neurocomputing Keyword: artificial immune system, multi-layered, graph planarization, estimation, feature, Full Text: PDF(476.3KB)>>
Summary: This paper presents a new multi-layered artificial immune system architecture using the ideas generated from the biological immune system for solving combinatorial optimization problems. The proposed methodology is composed of five layers. After expressing the problem as a suitable representation in the first layer, the search space and the features of the problem are estimated and extracted in the second and third layers, respectively. Through taking advantage of the minimized search space from estimation and the heuristic information from extraction, the antibodies (or solutions) are evolved in the fourth layer and finally the fittest antibody is exported. In order to demonstrate the efficiency of the proposed system, the graph planarization problem is tested. Simulation results based on several benchmark instances show that the proposed algorithm performs better than traditional algorithms. | ||||||||||
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