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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Online Access: | http://dx.doi.org/10.1155/2011/210918 |
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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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