An effective hybrid cuckoo search and genetic algorithm for constrained engineering design optimization

Abstract

This article presents an effective hybrid cuckoo search and genetic algorithm (HCSGA) for solving engineering design optimization problems involving problem-specific constraints and mixed variables such as integer, discrete and continuous variables. The proposed algorithm, HCSGA, is first applied to 13 standard benchmark constrained optimization functions and subsequently used to solve three well-known design problems reported in the literature. The numerical results obtained by HCSGA show competitive performance with respect to recent algorithms for constrained design optimization problems.

• cuckoo search
• genetic algorithm
• hybrid algorithm
• engineering design optimization

Acknowledgements

The first author would like to acknowledge the support from Thiagarajar College of Engineering, India, for the sabbatical leave to work at Monash University, Sunway Campus, Malaysia during the period during which this research was conducted.