IEICE TRANSACTIONS on Information
A Multi-Layered Immune System for Graph Planarization Problem
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.
- Publication
- IEICE TRANSACTIONS on Information Vol.E92-D No.12 pp.2498-2507
- Publication Date
- 2009/12/01
- Publicized
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.E92.D.2498
- Type of Manuscript
- PAPER
- Category
- Biocybernetics, Neurocomputing
Authors
Keyword
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Shangce GAO, Rong-Long WANG, Hiroki TAMURA, Zheng TANG, "A Multi-Layered Immune System for Graph Planarization Problem" in IEICE TRANSACTIONS on Information,
vol. E92-D, no. 12, pp. 2498-2507, December 2009, doi: 10.1587/transinf.E92.D.2498.
Abstract: 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.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E92.D.2498/_p
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@ARTICLE{e92-d_12_2498,
author={Shangce GAO, Rong-Long WANG, Hiroki TAMURA, Zheng TANG, },
journal={IEICE TRANSACTIONS on Information},
title={A Multi-Layered Immune System for Graph Planarization Problem},
year={2009},
volume={E92-D},
number={12},
pages={2498-2507},
abstract={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.},
keywords={},
doi={10.1587/transinf.E92.D.2498},
ISSN={1745-1361},
month={December},}
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TY - JOUR
TI - A Multi-Layered Immune System for Graph Planarization Problem
T2 - IEICE TRANSACTIONS on Information
SP - 2498
EP - 2507
AU - Shangce GAO
AU - Rong-Long WANG
AU - Hiroki TAMURA
AU - Zheng TANG
PY - 2009
DO - 10.1587/transinf.E92.D.2498
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E92-D
IS - 12
JA - IEICE TRANSACTIONS on Information
Y1 - December 2009
AB - 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.
ER -
English
