An Artificial Immune Network for Multimodal Optimisation

de Castro, L.N. and Timmis, J. (2002) An Artificial Immune Network for Multimodal Optimisation. In: 2002 Congress on Evolutionary Computation. Part of the 2002 IEEE World Congress on Computational Intelligence., 12-17 May 2002, Honolulu, HI. (The full text of this publication is not available from this repository)

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Official URL
http://dx.doi.org/10.1109/CEC.2002.1007011

Abstract

This paper presents the adaptation of an immune network model, originally proposed to perform information compression and data clustering, to solve multimodal function optimization problems. The algorithm is described, theoretically and empirically compared with similar approaches from the literature. The main features of the algorithm are automatic determination of the population size, combination of local with global search (exploitation plus exploration of the fitness landscape), defined convergence criterion, and capability of maintaining stable local optima solutions.

Item Type: Conference or workshop item (Paper)
Uncontrolled keywords: artificial immune systems, clonal selection, immune network, multimodal optimisation
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,
Divisions: Faculties > Science Technology and Medical Studies > School of Computing > Applied and Interdisciplinary Informatics Group
Faculties > Science Technology and Medical Studies > School of Computing > Applied and Interdisciplinary Informatics Group
Faculties > Science Technology and Medical Studies > School of Computing > Applied and Interdisciplinary Informatics Group
Depositing User: Mark Wheadon
Date Deposited: 24 Nov 2008 18:00
Last Modified: 04 May 2012 15:49
Resource URI: http://kar.kent.ac.uk/id/eprint/13792 (The current URI for this page, for reference purposes)
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