Paper Info
Title
Clonal selection algorithms: a comparative case study using effective mutation potentials
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.
Year
DOI
Venue
2005
10.1007/11536444_2
ICARIS
Keywords
Field
DocType
effective mutation potential,comparative case study,hp model,comparative study,protein structure prediction problem,numerical optimization problem,global better performance,important clonal selection algorithms,clonal selection algorithm,np-complete problem,toy problem,optimization task,evolutionary algorithms,protein structure prediction,np complete problems,evolutionary algorithm,np complete problem,pattern recognition
Protein structure prediction,NP-complete,Search algorithm,Comparative case,Evolutionary algorithm,Computer science,Algorithm,Artificial intelligence,Clonal selection,Optimization problem,Genetic algorithm,Machine learning
Conference
Volume
ISSN
ISBN
3627
0302-9743
3-540-28175-4
Citations 
PageRank 
References 
52
2.45
12
Authors
4
Name
Order
Citations
PageRank
vincenzo cutello155357.63
Giuseppe Narzisi215711.30
Giuseppe Nicosia347946.53
Mario Pavone421219.41