Scopus
A Novel Artificial Jellyfish Search Algorithm Improved with Detailed Local Search Strategy
Proceedings 6th International Conference on Computer Science and Engineering Ubmk 2021 · Ocak 2021
Makale Bilgileri
DergiProceedings 6th International Conference on Computer Science and Engineering Ubmk 2021
Yayın TarihiOcak 2021
Scopus ID2-s2.0-85125874137
Özet
Metaheuristic algorithms are frequently preferred algorithms for optimization problems in many different fields. The number of these algorithms inspired by natural phenomena is increasing day by day. Artificial Jellyfish Search Algorithm, inspired by the behavior of jellyfish in the ocean, is one of the new metaheuristic algorithms that have been proposed recently. In this study, two different search strategies were used together with a modification made in the active motion of the Artificial Jellyfish Search Algorithm, in the local search section, and the local search capability of the algorithm was thus developed. With this modification, it is aimed to preserve population diversity for a longer time. The proposed algorithm has been tested for 10, 30, and 50 dimensions on single-objective CEC2017 benchmark functions. The results obtained were compared with the standard algorithm and algorithms selected from the literature and interpreted with the help of statistical tests. It has been determined that the proposed algorithm outperforms the standard algorithm and becomes competitive with other algorithms in the literature thanks to the modification made.
Yazarlar (2)
1
Gülnur Yildizdan
2
Omer Kaan Baykan
Anahtar Kelimeler
Artificial jellyfish search algorithm
CEC2017 benchmarkfunctions
Continuous optimization
Global optimization
Metaheuristic algorithm
Kurumlar
Konya Technical University
Konya Turkey
Selçuk Üniversitesi
Selçuklu Turkey
Metrikler
6
Atıf
2
Yazar
5
Anahtar Kelime