A Hybrid CS/PSO Algorithm for Global Optimization

摘要

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 L£vy 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.