A Multi-Layered Immune System for Graph Planarization Problem

Shangce GAO  Rong-Long WANG  Hiroki TAMURA  Zheng TANG  

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
artificial immune system,  multi-layered,  graph planarization,  estimation,  feature,  

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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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