Journal of Global Optimization
Advances in Multi-Objective Nature Inspired Computing
Advances in Multi-Objective Nature Inspired Computing
Engineering Optimization: An Introduction with Metaheuristic Applications
Engineering Optimization: An Introduction with Metaheuristic Applications
Nature-Inspired Metaheuristic Algorithms: Second Edition
Nature-Inspired Metaheuristic Algorithms: Second Edition
Modified cuckoo search algorithm for unconstrained optimization problems
ECC'11 Proceedings of the 5th European conference on European computing conference
Metaheuristic optimization: algorithm analysis and open problems
SEA'11 Proceedings of the 10th international conference on Experimental algorithms
A novel quantum inspired cuckoo search for knapsack problems
International Journal of Bio-Inspired Computation
A refactoring method for cache-efficient swarm intelligence algorithms
Information Sciences: an International Journal
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This paper presents the hybrid approach of two nature inspired metaheuristic algorithms; Cuckoo Search (CS) and Particle Swarm Optimization (PSO) for solving optimization problems. Cuckoo birds lay their own eggs to other host birds. If the host birds discover the alien birds, they will leave the nest or throw the egg away. Cuckoo birds migrate to the environments that reduce the chance of their eggs to be discovered by the host birds. In standard CS, cuckoo birds experience new places by the Lévy Flight. In the proposed hybrid algorithm, cuckoo birds are aware of each other positions and make use of swarm intelligence in PSO in order to reach to better solutions. Experimental results are examined with some standard benchmark functions and the results show a promising performance of this algorithm.