Cuckoo Search and Genetic Algorithm Hybrid Schemes for Optimization Problems

Authors

Mohamed Abdel-Baset, Department of Operations Research, Faculty of Computers and Informatics, Zagazig University, El-Zera Square, Zagazig, Sharqiyah, Egypt.Follow
Ibrahim Hezam, Department of computer, Faculty of Education, Ibb University, Ibb city, Yemen.Follow

Author Country (or Countries)

Egypt.

Abstract

In this paper, two hybrid schemes using cuckoo search algorithm and genetic algorithm are proposed. In the two hybrid schemes, the algorithm consists of two phases in the first phase, CS (or GA) explores the search space. In the second phase, to improve global search and get rid of trapping into several local optima. The novel hybrid algorithms are applied to solve 15 benchmark functions chosen from literature. The simulation results and comparison with classical CS and GA algorithms confirm the effectiveness of the proposed algorithms in solving various benchmark optimization functions.

Digital Object Identifier (DOI)

http://dx.doi.org/10.18576/amis/100337

Recommended Citation

Abdel-Baset, Mohamed and Hezam, Ibrahim (2016) "Cuckoo Search and Genetic Algorithm Hybrid Schemes for Optimization Problems," Applied Mathematics & Information Sciences: Vol. 10: Iss. 3, Article 37.
DOI: http://dx.doi.org/10.18576/amis/100337
Available at: https://digitalcommons.aaru.edu.jo/amis/vol10/iss3/37