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Linkage in Evolutionary Computation pp 285–314Cite as

Symbiotic Evolution to Avoid Linkage Problem

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 157))

Abstract

In this chapter, we introduce Symbiotic Evolutionary Algorithm (SEA) as a template for search and optimization based on partially specified chromosomes and symbiotic combination operator. We show that in contrast to genetic algorithms with traditional recombination operators, this template will not be bound to linkage problems. We present three implementations of this template: first, as a pure algorithm for search and optimization, second, as an artificial immune system, and third, as an algorithm for classifier rule base evolution, and compare implementation results and feature lists with similar algorithms.

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  1. Sharif University of Technology, Iran

    Ramin Halavati & Saeed Bagheri Shouraki

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  1. Ramin Halavati
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  2. Saeed Bagheri Shouraki
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Ying-ping Chen Meng-Hiot Lim

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Halavati, R., Shouraki, S.B. (2008). Symbiotic Evolution to Avoid Linkage Problem. In: Chen, Yp., Lim, MH. (eds) Linkage in Evolutionary Computation. Studies in Computational Intelligence, vol 157. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85068-7_12

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