Design of Fixed and Ladder Mutation Factor-Based Clonal Selection Algorithm for Solving Unimodal and Multimodal Functions

Clonal selection algorithms (CSAs) is a special class of immune algorithms (IA), inspired by the clonal selection principle of the human immune system. To improve the algorithm's ability to perform better, this CSA has been modified by implementing two new concepts called fixed mutation factor...

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Main Authors: Suresh Chittineni, A. N. S. Pradeep, Dinesh Godavarthi, Suresh Chandra Satapathy, S. Mohan Krishna, P. V. G. D. Prasad Reddy
Format: Article
Language:English
Published: Hindawi Limited 2011-01-01
Series:Applied Computational Intelligence and Soft Computing
Online Access:http://dx.doi.org/10.1155/2011/210918
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spelling doaj-f475f75e73b146b7bda8392666dc523f2020-11-24T23:19:40ZengHindawi LimitedApplied Computational Intelligence and Soft Computing1687-97241687-97322011-01-01201110.1155/2011/210918210918Design of Fixed and Ladder Mutation Factor-Based Clonal Selection Algorithm for Solving Unimodal and Multimodal FunctionsSuresh Chittineni0A. N. S. Pradeep1Dinesh Godavarthi2Suresh Chandra Satapathy3S. Mohan Krishna4P. V. G. D. Prasad Reddy5Anil Neerukonda Institute of Technology and Sciences, Visakhapatnam, Andhra Pradesh, IndiaAnil Neerukonda Institute of Technology and Sciences, Visakhapatnam, Andhra Pradesh, IndiaAnil Neerukonda Institute of Technology and Sciences, Visakhapatnam, Andhra Pradesh, IndiaAnil Neerukonda Institute of Technology and Sciences, Visakhapatnam, Andhra Pradesh, IndiaGitam University, Visakhapatnam, IndiaAndhra University Engineering College, Visakhapatnam, Andhra Pradesh, IndiaClonal selection algorithms (CSAs) is a special class of immune algorithms (IA), inspired by the clonal selection principle of the human immune system. To improve the algorithm's ability to perform better, this CSA has been modified by implementing two new concepts called fixed mutation factor and ladder mutation factor. Fixed mutation factor maintains a constant factor throughout the process, where as ladder mutation factor changes adaptively based on the affinity of antibodies. This paper compared the conventional CLONALG, with the two proposed approaches and tested on several standard benchmark functions. Experimental results empirically show that the proposed methods ladder mutation-based clonal selection algorithm (LMCSA) and fixed mutation clonal selection algorithm (FMCSA) significantly outperform the existing CLONALG method in terms of quality of the solution, convergence speed, and solution stability.http://dx.doi.org/10.1155/2011/210918
collection DOAJ
language English
format Article
sources DOAJ
author Suresh Chittineni
A. N. S. Pradeep
Dinesh Godavarthi
Suresh Chandra Satapathy
S. Mohan Krishna
P. V. G. D. Prasad Reddy
spellingShingle Suresh Chittineni
A. N. S. Pradeep
Dinesh Godavarthi
Suresh Chandra Satapathy
S. Mohan Krishna
P. V. G. D. Prasad Reddy
Design of Fixed and Ladder Mutation Factor-Based Clonal Selection Algorithm for Solving Unimodal and Multimodal Functions
Applied Computational Intelligence and Soft Computing
author_facet Suresh Chittineni
A. N. S. Pradeep
Dinesh Godavarthi
Suresh Chandra Satapathy
S. Mohan Krishna
P. V. G. D. Prasad Reddy
author_sort Suresh Chittineni
title Design of Fixed and Ladder Mutation Factor-Based Clonal Selection Algorithm for Solving Unimodal and Multimodal Functions
title_short Design of Fixed and Ladder Mutation Factor-Based Clonal Selection Algorithm for Solving Unimodal and Multimodal Functions
title_full Design of Fixed and Ladder Mutation Factor-Based Clonal Selection Algorithm for Solving Unimodal and Multimodal Functions
title_fullStr Design of Fixed and Ladder Mutation Factor-Based Clonal Selection Algorithm for Solving Unimodal and Multimodal Functions
title_full_unstemmed Design of Fixed and Ladder Mutation Factor-Based Clonal Selection Algorithm for Solving Unimodal and Multimodal Functions
title_sort design of fixed and ladder mutation factor-based clonal selection algorithm for solving unimodal and multimodal functions
publisher Hindawi Limited
series Applied Computational Intelligence and Soft Computing
issn 1687-9724
1687-9732
publishDate 2011-01-01
description Clonal selection algorithms (CSAs) is a special class of immune algorithms (IA), inspired by the clonal selection principle of the human immune system. To improve the algorithm's ability to perform better, this CSA has been modified by implementing two new concepts called fixed mutation factor and ladder mutation factor. Fixed mutation factor maintains a constant factor throughout the process, where as ladder mutation factor changes adaptively based on the affinity of antibodies. This paper compared the conventional CLONALG, with the two proposed approaches and tested on several standard benchmark functions. Experimental results empirically show that the proposed methods ladder mutation-based clonal selection algorithm (LMCSA) and fixed mutation clonal selection algorithm (FMCSA) significantly outperform the existing CLONALG method in terms of quality of the solution, convergence speed, and solution stability.
url http://dx.doi.org/10.1155/2011/210918
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