Clonal Selection Algorithm with Dynamic Population Size for Bimodal Search Spaces

In this article an Immune Algorithm (IA) with dynamic population size is presented. Unlike previous IAs and Evolutionary Algorithms (EAs), in which the population dimension is constant during the evolutionary process, the population size is computed adaptively according to a cloning threshold. This not only enhances convergence speed but also gives more chance to escape from local minima. Extensive simulations are performed on trap functions and their performances are compared both quantitatively and statistically with other immune and evolutionary optmization methods.

[1]  Vincenzo Cutello,et al.  Immune Algorithms with Aging Operators for the String Folding Problem and the Protein Folding Problem , 2005, EvoCOP.

[2]  V. Cutello,et al.  An Immune Algorithm with Hyper – Macromutations for the 2 D Hydrophilic-Hydrophobic Model , 2022 .

[3]  Vincenzo Cutello,et al.  Clonal Selection Algorithms: A Comparative Case Study Using Effective Mutation Potentials , 2005, ICARIS.

[4]  Vincenzo Cutello,et al.  An immune algorithm with hyper-macromutations for the Dill's 2D hydrophobic-hydrophilic model , 2004, Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753).

[5]  Vincenzo Cutello,et al.  The Clonal Selection Principle for In Silico and In Vitro Computing , 2005 .

[6]  Vincenzo Cutello,et al.  Exploring the Capability of Immune Algorithms: A Characterization of Hypermutation Operators , 2004, ICARIS.

[7]  Jonathan Timmis,et al.  Artificial immune systems - a new computational intelligence paradigm , 2002 .

[8]  Leandro Nunes de Castro,et al.  Recent Developments In Biologically Inspired Computing , 2004 .

[9]  Fernando José Von Zuben,et al.  Learning and optimization using the clonal selection principle , 2002, IEEE Trans. Evol. Comput..

[10]  Thomas Bäck,et al.  An analysis of the behavior of simplified evolutionary algorithms on trap functions , 2003, IEEE Trans. Evol. Comput..

[11]  Jens Gottlieb,et al.  Evolutionary Computation in Combinatorial Optimization , 2006, Lecture Notes in Computer Science.

[12]  Vincenzo Cutello,et al.  Real coded clonal selection algorithm for unconstrained global optimization using a hybrid inversely proportional hypermutation operator , 2006, SAC.