2017 Cilt 22 Sayı 2

Permanent URI for this collectionhttps://hdl.handle.net/11452/12031

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Browsing by Subject "Clonal selection algorithm"

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    Performance study of bat algorithm and clonal selection algorithm for optimization tasks
    (Uludağ Üniversitesi, 2017-06-12) Ülker, Ezgi Deniz
    Evolutionary algorithms are preferred by many researchers in different areas for optimization tasks. It is quite important to find optimum points of problems with less number of iterations. In this paper, performance analysis of two powerful optimization algorithms; bat algorithm and clonal selection algorithm are studied using well-known benchmark functions. The experimental results show that bat algorithm outperforms clonal selection algorithm on most of the selected problems. It is also seen that bat algorithm can produce high quality results even at the first stages of iterations. This paper can be used as guidance of performance comparisons for future studies.