Modified cuckoo search algorithm for solving global optimization problems

Abstract

In this paper, modified cuckoo search algorithm (MCSA) is presented for solving global optimization problems. Cuckoo Search Algorithm (CSA) was proposed by Yang and Deb in 2009. To date, work on this algorithm has significantly increased, and the CSA has succeeded in having its rightful place among other optimization methodologies. The modified version of CSA based on replacing the random selection with tournament selection. Thus, the probability of better results is increased, thereby avoiding the premature convergence. The validation of the performance is determined by applying several benchmarks. The results of experimental simulations are indicated that the MCSA performs better than standard CSA.