抄録
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.
本文言語 | 英語 |
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ページ(範囲) | 2498-2507 |
ページ数 | 10 |
ジャーナル | IEICE Transactions on Information and Systems |
巻 | E92-D |
号 | 12 |
DOI | |
出版ステータス | 出版済み - 2009 |
ASJC Scopus 主題領域
- ソフトウェア
- ハードウェアとアーキテクチャ
- コンピュータ ビジョンおよびパターン認識
- 電子工学および電気工学
- 人工知能