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Surrogate-Assisted Artificial Immune Systems for Expensive Optimization Problems [chapter]

Heder S., Leonardo G., Helio J. C. Barbos
2009 Evolutionary Computation  
Section 2 gives a formulation for the optimization problems considered here. AISs are presented in Section 3.  ...  This scheme of adaptation is known as clonal selection and affinity maturation by hypermutation or, more simply, clonal selection (Garrett, 2004) .  ...  Clonal selection algorithm Based on the clonal selection theory, de Castro and Von Zuben proposed an AIS algorithm that performs computational optimization and pattern recognition tasks.  ... 
doi:10.5772/9618 fatcat:t4bg7sxhkvbtdbzf76fzy4tjta

A multi-objective algorithm for DS-CDMA code design based on the clonal selection principle

Daniel Stevens, Sanjoy Das, Bala Natarajan
2005 Proceedings of the 2005 conference on Genetic and evolutionary computation - GECCO '05  
This paper proposes a new algorithm based on the clonal selection principle for the design of spreading codes for DS-CDMA.  ...  The algorithm maintains a repertoire of codes that are subject to cloning and undergo a process of affinity maturation to obtain better codes.  ...  An algorithm by de Castro and von Zuben, CLONALG (CLONal selection ALGorithm) [5] offers a versatile algorithm for learning as well as stochastic optimization.  ... 
doi:10.1145/1068009.1068345 dblp:conf/gecco/StevensDN05 fatcat:xmls4hfi2rbsnhhlgsub2hjaku


Jereesh A S .
2013 International Journal of Research in Engineering and Technology  
Results: In this work, we have proposed Clonal selection algorithm for identifying optimal gene regulatory network.  ...  Since the problem has multiple solutions, we have to identify an optimized solution. Evolutionary algorithms have been used to solve such problems.  ...  We propose to employ an optimization technique known as Clonal selection algorithm, which is faster than the genetic algorithm.  ... 
doi:10.15623/ijret.2013.0208006 fatcat:h5gcter5vfh6pagbsz4oqcjnb4

High Performance Immune Clonal Algorithm for Solving Large Scale TSP [chapter]

Fang Liu, Yutao Qi, Jingjing Ma, Maoguo Gong, Ronghua Shang, Yangyang Li, Licheng Jiao
2010 Traveling Salesman Problem, Theory and Applications  
Parallel immune memory clonal selection algorithm for large scale TSP Traveling salesman problem (TSP) is a classical combinatorial optimization problem, with a strong engineering background and extensive  ...  Immune clonal selection algorithm Clonal selection algorithm is an important type of immune optimization algorithm, and it has been widely used in the artificial immune system.  ...  This book is a collection of current research in the application of evolutionary algorithms and other optimal algorithms to solving the TSP problem.  ... 
doi:10.5772/13034 fatcat:hpzuqvzlq5ce3kid3e2om6zcsm

Clonal selection based genetic algorithm for workflow service selection

Simone A. Ludwig
2012 2012 IEEE Congress on Evolutionary Computation  
Experimental results show that the clonal selection based genetic algorithm achieves much higher fitness values for the workflow selection problem than standard genetic algorithm.  ...  Quality of Service (QoS) aware service selection of workflows is a very important aspect for service-oriented systems.  ...  An improved clonal selection algorithm that deals with numerical optimization problems was introduced in [27] .  ... 
doi:10.1109/cec.2012.6256465 dblp:conf/cec/Ludwig12 fatcat:7bv2pybp7jg4znpzpyslzjol3u

Baldwinian learning in clonal selection algorithm for optimization

Maoguo Gong, Licheng Jiao, Lining Zhang
2010 Information Sciences  
In this paper, based on the Baldwin effect, an improved clonal selection algorithm, Baldwinian Clonal Selection Algorithm, termed as BCSA, is proposed to deal with optimization problems.  ...  Most immune system inspired optimization algorithms are based on the applications of clonal selection and hypermutation, and known as clonal selection algorithms.  ...  Accordingly, a novel immune algorithm, Baldwinian Clonal Selection Algorithm, termed as BCSA, is proposed to solve optimization problems.  ... 
doi:10.1016/j.ins.2009.12.007 fatcat:yupvouymlzfnndrjxoo4un37yi

Topology Optimization Based on Immune Algorithm and Multigrid Method

Kota Watanabe, F. Campelo, H. Igarashi
2007 IEEE transactions on magnetics  
Moreover, the present method uses a new optimization algorithm, based on the artificial immune systems paradigm, in which the multilevel search is carried out.  ...  Index Terms-Finite-element method (FEM), immune algorithm, multigrid method, topology optimization.  ...  The proposed approach, called clonal selection algorithm for topology optimization (TopCSA), uses a simple 2-D binary matrix for representing the search space.  ... 
doi:10.1109/tmag.2006.892259 fatcat:rufzk6roabdf7imzpijx5a57aq


Ozlem Kilic, Q. M. Nguyen
2010 Progress in Electromagnetics Research B  
This paper investigates the use of clonal selection principles based on our immune system for optimization applications in electromagnetics.  ...  The performance of the algorithm is investigated for well known mathematical test functions and its potential is demonstrated in the context of the design of a radar absorbing material and a planar phased  ...  In [12] , a real coded clonal selection algorithm is proposed eliminating the need to convert the optimization space to the binary domain.  ... 
doi:10.2528/pierb10010701 fatcat:7fieztkgqneernka6xv47uashi

An Artificial Immune System Approach to Associative Classification [chapter]

Samir A. Mohamed Elsayed, Sanguthevar Rajasekaran, Reda A. Ammar
2012 Lecture Notes in Computer Science  
This paper introduces AC-CS, a novel AC algorithm, inspired by the clonal selection of the immune system.  ...  However, traditional AC algorithms typically search for all possible association rules to find a representative subset of those rules.  ...  A brief summary of one of the major AIS algorithms namely, the clonal selection algorithm, is also presented.  ... 
doi:10.1007/978-3-642-31125-3_13 fatcat:kg32k5c3h5bndeyauvjelhb3pe

Reconstructing the evolutionary history of a BCR lineage with minimum spanning tree and clonotype abundances [article]

Nika Abdollahi, Anne de Septenville, Frederic Davi, Juliana Silva Bernardes
2022 bioRxiv   pre-print
In a B cell lineage, cells with a higher antigen affinity will undergo clonal expansion, while those with a lower affinity will not proliferate and probably be eliminated.  ...  B cell receptor (BCR) genes exposed to an antigen undergo somatic hypermutations and Darwinian antigen selection, generating a large BCR-antibody diversity.  ...  Acknowledgements Authors are grateful to Lucile Jeusset and Thibaud Verny for their insightful comments and fruitful discussion.  ... 
doi:10.1101/2022.02.27.481992 fatcat:74ratmzmu5affowidaumcu7zba

Improved Pattern Recognition with Artificial Clonal Selection? [chapter]

Jennifer A. White, Simon M. Garrett
2003 Lecture Notes in Computer Science  
In this paper, we examine the clonal selection algorithm CLONALG and the suggestion that it is suitable for pattern recognition.  ...  CLONALG is tested over a series of binary character recognition tasks and its performance compared to a set of basic binary matching algorithms.  ...  The Hamming methods are considerably faster than both clonal selection algorithms running at only O(E 2 M +T (M L)).  ... 
doi:10.1007/978-3-540-45192-1_18 fatcat:n76oqhxulnftdkleevqs3bivtu

Germinal Center Optimization Algorithm

Carlos Villaseñor, Nancy Arana-Daniel, Alma Y. Alanis, Carlos López-Franco, Esteban A. Hernandez-Vargas
2018 International Journal of Computational Intelligence Systems  
We show that the proposal has a statistically significant improvement over the other algorithms for low dimensionality problems.  ...  To show the performance, we include a benchmark with the comparison of our approach versus some of the state-of-the-art bio-inspired optimization algorithms.  ...  Note that GCO is faster than GSA, GA and ABC. PSO is the fastest algorithm in the tests. Finally, we claim that GCO is a good option for low dimension problems.  ... 
doi:10.2991/ijcis.2018.25905179 fatcat:shnl3lhigvcmvnvjlz3o23ecf4

Genetic Algorithm with adaptive elitist-population strategies for multimodal function optimization

Yong Liang, Kwong-Sak Leung
2011 Applied Soft Computing  
This technique allows unimodal function optimization methods to be extended to efficiently explore multiple optima of multimodal problems.  ...  Incorporation of the new multimodal technique in any known evolutionary algorithm leads to a multimodal version of the algorithm.  ...  The authors would like to thank the anonymous reviewers for their constructive comments and suggestions which have significantly improved this paper.  ... 
doi:10.1016/j.asoc.2010.06.017 fatcat:fhxvgnupejdp5gtwfadjbdohvm

An Immune Clonal Selection Algorithm for Synthetic Signature Generation

Mofei Song, Zhengxing Sun
2014 Mathematical Problems in Engineering  
To overcome this problem, this paper proposes a detector generation based clonal selection algorithm for synthetic signature set generation.  ...  Then the clonal selection algorithm is used to expand and optimize the overall signature set.  ...  Conclusion In this paper, we present a novel clonal selection algorithm for synthetic sample generation.  ... 
doi:10.1155/2014/324645 fatcat:h3m7fl2shjeylhddigknnupwpa

Brief Review of Computational Intelligence Algorithms [article]

Satyarth Vaidya, Arshveer Kaur, Lavika Goel
2019 arXiv   pre-print
Computational Intelligence algorithms have gained a lot of attention of researchers in the recent years due to their ability to deliver near optimal solutions.  ...  Algorithm Eil51 Eil101 Clonal Selection 94.62 2500 2  ...  Initial parameter tuning offers a wide range of search behaviors. A living multi agent algorithm designed for continuous optimization problems.  ... 
arXiv:1901.00983v3 fatcat:hpesiwjf6zfu3ico77uxmnzcze
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