Work place: Department of computer, Faculty of Education, Ibb University, Ibb city, Yemen
E-mail: ibrahizam.math@gmail.com
Website:
Research Interests: Artificial Intelligence, Computer Architecture and Organization, Decision Support System, Data Structures and Algorithms, Combinatorial Optimization
Biography
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.
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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