Clonal Selection Algorithms: A Comparative Case Study Using Effective Mutation Potentials View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2005

AUTHORS

Vincenzo Cutello , Giuseppe Narzisi , Giuseppe Nicosia , Mario Pavone

ABSTRACT

This paper presents a comparative study of two important Clonal Selection Algorithms (CSAs): CLONALG and opt-IA. To deeply understand the performance of both algorithms, we deal with four different classes of problems: toy problems (one-counting and trap functions), pattern recognition, numerical optimization problems and NP-complete problem (the 2D HP model for protein structure prediction problem). Two possible versions of CLONALG have been implemented and tested. The experimental results show a global better performance of opt-IA with respect to CLONALG. Considering the results obtained, we can claim that CSAs represent a new class of Evolutionary Algorithms for effectively performing searching, learning and optimization tasks. More... »

PAGES

13-28

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/11536444_2

DOI

http://dx.doi.org/10.1007/11536444_2

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1019780999


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