Cuckoo Search via Lévy flights

In this paper, we intend to formulate a new meta-heuristic algorithm, called Cuckoo Search (CS), for solving optimization problems. This algorithm is based on the obligate brood parasitic behaviour of some cuckoo species in combination with the Lévy flight behaviour of some birds and fruit flies. We validate the proposed algorithm against test functions and then compare its performance with those of genetic algorithms and particle swarm optimization. Finally, we discuss the implication of the results and suggestion for further research.

[1]  R. Chattopadhyay A study of test functions for optimization algorithms , 1971 .

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

[3]  Fabio Schoen,et al.  A wide class of test functions for global optimization , 1993, J. Glob. Optim..

[4]  Barbara Webb,et al.  Swarm Intelligence: From Natural to Artificial Systems , 2002, Connect. Sci..

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

[6]  Christian Blum,et al.  Metaheuristics in combinatorial optimization: Overview and conceptual comparison , 2003, CSUR.

[7]  K.M. Passino,et al.  Stability analysis of social foraging swarms , 2004, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[8]  M. Shlesinger Mathematical physics: Search research , 2006, Nature.

[9]  Ilya Pavlyukevich Lévy flights, non-local search and simulated annealing , 2007, J. Comput. Phys..

[10]  A. Reynolds,et al.  Free-Flight Odor Tracking in Drosophila Is Consistent with an Optimal Intermittent Scale-Free Search , 2007, PloS one.

[11]  Clifford T. Brown,et al.  Lévy Flights in Dobe Ju/’hoansi Foraging Patterns , 2007 .

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

[13]  I. Pavlyukevich Cooling down Lévy flights , 2007, cond-mat/0701651.

[14]  Mauro Birattari,et al.  Swarm Intelligence , 2012, Lecture Notes in Computer Science.

[15]  Seppo J. Ovaska,et al.  A general framework for statistical performance comparison of evolutionary computation algorithms , 2006, Inf. Sci..

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

[17]  P. Barthelemy,et al.  A Lévy flight for light , 2008, Nature.

[18]  World Congress on Nature & Biologically Inspired Computing, NaBIC 2009, 9-11 December 2009, Coimbatore, India , 2009, NaBIC.