Ibrahim M. Hezam

Work place: Department of computer, Faculty of Education, Ibb University, Ibb city, Yemen

E-mail: ibrahizam.math@gmail.com


Research Interests: Artificial Intelligence, Computer Architecture and Organization, Decision Support System, Data Structures and Algorithms, Combinatorial Optimization


Ibrahim M. Hezam obtained his B.Sc. in 2003 in Mathematics from IBB University, IBB, Yemen; His M.Sc. in Pure Mathematics (Operations Research) from Helwan University, Egypt, in 2011.

Currently, he is a Ph.D. student in Department of Operations Research and Decision Support, Faculty of Computers & Information, Menoufia University, Egypt. His research interests are metaheuristic optimization methods, artificial intelligence, and decision support systems.

Author Articles
Cuckoo Search Algorithm for Stellar Population Analysis of Galaxies

By Mohamed Abdel-Baset Ibrahim M. Selim Ibrahim M. Hezam

DOI: https://doi.org/10.5815/ijitcs.2015.11.04, Pub. Date: 8 Oct. 2015

The cuckoo search algorithm (CS) is a simple and effective global optimization algorithm. It has been applied to solve a wide range of real-world optimization problem. In this paper, an improved Cuckoo Search Algorithm (ICS) is presented for determining the age and relative contribution of different stellar populations in galaxies. The results indicate that the proposed method performs better than, or at least comparable to state-of-the-art method from literature when considering the quality of the solutions obtained. The proposed algorithm will be applied to integrated color of galaxy NGC 3384. Simulation results further demonstrate the proposed method is very effective. The study revealed that cuckoo search can successfully be applied to a wide range of stellar population and space optimization problems.

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