Cuckoo Search Algorithm for Stellar Population Analysis of Galaxies

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Mohamed Abdel-Baset 1,* Ibrahim M. Selim 2 Ibrahim M. Hezam 3

1. Department of Operations Research, faculty of Computers and Informatics, Zagazig University, El-ZeraSquare, Zagazig, Sharqiyah, Egypt

2. National Research Institute of Astronomy and Geophysics (NRIAG), 11421 Helwan, Cairo, Egypt

3. Department of computer, Faculty of Education, Ibb University, Ibb city, Yemen

* Corresponding author.


Received: 10 Feb. 2015 / Revised: 10 Jun. 2015 / Accepted: 24 Aug. 2015 / Published: 8 Oct. 2015

Index Terms

Cuckoo search algorithm, Meta-heuristics, Optimization, Stellar Population, Galaxies


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.

Cite This Paper

Mohamed Abdel-Baset, Ibrahim M. Selim, Ibrahim M. Hezam, "Cuckoo Search Algorithm for Stellar Population Analysis of Galaxies", International Journal of Information Technology and Computer Science(IJITCS), vol.7, no.11, pp.29-33, 2015. DOI:10.5815/ijitcs.2015.11.04


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