A Novel Cuckoo Search with Chaos Theory and Elitism Scheme

This study proposes a novel chaotic cuckoo search (CCS) optimization method by introducing chaotic theory into cuckoo search (CS) algorithm. In CCS, chaos characteristics are combined with the CS with the intention of further enhancing its performance. Further, the elitism scheme is incorporated into CCS in order to preserve the best cuckoos. In the CCS method, twelve chaotic maps are applied to tune the step size of the cuckoos used in the original CS method. Twenty-two benchmark functions are utilized to investigate the efficiency of CCS. The results show that the performance of CCS together with a suitable chaotic map are comparable as well as superior to that of the CS and other metaheuristic algorithms.

[1]  Xin-She Yang,et al.  Firefly algorithm with chaos , 2013, Commun. Nonlinear Sci. Numer. Simul..

[2]  Zong Woo Geem,et al.  A New Heuristic Optimization Algorithm: Harmony Search , 2001, Simul..

[3]  Amir Hossein Alavi,et al.  An effective krill herd algorithm with migration operator in biogeography-based optimization , 2014 .

[4]  Hans-Georg Beyer,et al.  The Theory of Evolution Strategies , 2001, Natural Computing Series.

[5]  Xin-She Yang,et al.  Metaheuristic Applications in Structures and Infrastructures , 2013 .

[6]  Riccardo Poli,et al.  Particle swarm optimization , 1995, Swarm Intelligence.

[7]  Manuel López-Ibáñez,et al.  Ant colony optimization , 2010, GECCO '10.

[8]  Minghao Yin,et al.  Multiobjective Binary Biogeography Based Optimization for Feature Selection Using Gene Expression Data , 2013, IEEE Transactions on NanoBioscience.

[9]  John Maynard Smith,et al.  The Theory of Evolution , 1958 .

[10]  Amir Hossein Gandomi,et al.  A new improved krill herd algorithm for global numerical optimization , 2014, Neurocomputing.

[11]  Amir Hossein Alavi,et al.  Krill herd: A new bio-inspired optimization algorithm , 2012 .

[12]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[13]  H. H. Newman The Theory of Evolution , 1917, Botanical Gazette.

[14]  Minghao Yin,et al.  Animal migration optimization: an optimization algorithm inspired by animal migration behavior , 2014, Neural Computing and Applications.

[15]  Xin-She Yang,et al.  Chaos-enhanced accelerated particle swarm optimization , 2013, Commun. Nonlinear Sci. Numer. Simul..

[16]  Shumeet Baluja,et al.  A Method for Integrating Genetic Search Based Function Optimization and Competitive Learning , 1994 .

[17]  Xin-She Yang,et al.  Engineering optimisation by cuckoo search , 2010, Int. J. Math. Model. Numer. Optimisation.

[18]  Amir Hossein Gandomi,et al.  A chaotic particle-swarm krill herd algorithm for global numerical optimization , 2013, Kybernetes.

[19]  Goldberg,et al.  Genetic algorithms , 1993, Robust Control Systems with Genetic Algorithms.

[20]  Xin-She Yang,et al.  Nature-Inspired Metaheuristic Algorithms , 2008 .

[21]  A. Gandomi,et al.  Imperialist competitive algorithm combined with chaos for global optimization , 2012 .

[22]  Luo Liu,et al.  Hybridizing harmony search with biogeography based optimization for global numerical optimization , 2013 .

[23]  Xiangtao Li,et al.  An opposition-based differential evolution algorithm for permutation flow shop scheduling based on diversity measure , 2013, Adv. Eng. Softw..

[24]  Rainer Storn,et al.  Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces , 1997, J. Glob. Optim..

[25]  Muhammad Khurram Khan,et al.  An effective memetic differential evolution algorithm based on chaotic local search , 2011, Inf. Sci..

[26]  Amir Hossein Gandomi,et al.  Chaotic Krill Herd algorithm , 2014, Inf. Sci..

[27]  Amir Hossein Gandomi,et al.  Hybrid krill herd algorithm with differential evolution for global numerical optimization , 2014, Neural Computing and Applications.

[28]  Minghao Yin,et al.  Application of Differential Evolution Algorithm on Self-Potential Data , 2012, PloS one.

[29]  Amir Hossein Gandomi,et al.  Stud krill herd algorithm , 2014, Neurocomputing.