An artificial immune network for multimodal function optimization

Leandro N. De Castro, Jon Timmis

Research output: Contribution to conferencePaperpeer-review

630 Citations (SciVal)


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 include: 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 locating and maintaining stable local optima solutions.

Original languageEnglish
Number of pages6
Publication statusPublished - 2002
Event2002 Congress on Evolutionary Computation, CEC 2002 - Honolulu, HI, United States of America
Duration: 12 May 200217 May 2002


Conference2002 Congress on Evolutionary Computation, CEC 2002
Country/TerritoryUnited States of America
CityHonolulu, HI
Period12 May 200217 May 2002

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