Background: Cuckoo Search Algorithm (CSA) was introduced by Yang and Deb in
2009. It considers as one of the most successful in various fields compared with the metaheuristic
algorithms. However, random selection is used in the original CSA which means there is no high
chance for the best solution to select, also, losing the diversity.
Methods: In this paper, the Modified Cuckoo Search Algorithm (MCSA) is proposed to enhance
the performance of CSA for unconstrained optimization problems. MCSA is focused on the default
selection scheme of CSA (i.e. random selection) which is replaced with tournament selection. So,
MCSA will increase the probability of better results and avoid the premature convergence. A set of
benchmark functions is used to evaluate the performance of MCSA.
Results: The experimental results showed that the performance of MCSA outperformed standard
CSA and the existing literature methods.
Conclusion: The MCSA provides the diversity by using the tournament selection scheme because
it gives the opportunity to all solutions to participate in the selection process.