Araştırma Makalesi

Improved Whale Optimization Algorithm Based On π Number

Cilt: 4 Sayı: 1 30 Haziran 2020
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Improved Whale Optimization Algorithm Based On π Number

Öz

In this study, an improved version is presented as a result of experiments performed on the whale optimization algorithm (WOA) in the literature. As a result of the experiments, number was added to the coefficient vector of the algorithm. The developed WOA algorithm based on the number of was adapted to test problems. The 23 most common Benchmark functions have been selected as test problems. In line with the results, it was observed that the exploitation and exploration phases of the WOA developed. The success of the results has proven itself in comparison with other algorithms.

Anahtar Kelimeler

Teşekkür

Thank to Dr. Seyedali Mirjalili for his scientifically motivating research and for clearly sharing them with everyone.

Kaynakça

  1. [1] Alatas, B. “ACROA: Artificial Chemical Reaction Optimization Algorithm for global optimization.” Expert Systems with Applications 38, 13170–13180, 2011.
  2. [2] Hatamlou A. “Black hole: a new heuristic optimization approach for data clustering,” Inf Sci, 222:175–184. 2013.
  3. [3] Huang F, Wang L, He Q. “An effective co-evolutionary differential evolution for constrained optimization,” Appl Math Computation, 186(1), 340–356, 2007.
  4. [4] Kirkpatrick S, Gelatt CD, Vecchi MP. “Optimization by simulated annealing,” Science, 220(4598), 671–680. 1983.
  5. [5] CernýV. “Thermodynamical approach to the traveling salesman problem: an efficient simulation algorithm,” Journal of Optimization Theory and Applications, 45(1), 41–51, 1985.
  6. [6] Rashedi E, Nezamabadi-Pour H, Saryazdi S. “GSA: a gravitational search algorithm,” Inf Sci, 179,2232–2248,2009.
  7. [7] Mirjalili, S., Mirjalili, S. M., & Hatamlou, “A. Multi-verse optimizer: a nature-inspired algorithm for global optimization” Neural Computing and Applications, 27(2), 495-513. 2016.
  8. [8] Dorigo M, Birattari M, Stutzle T. “Ant colony optimization,” IEEE Comput Intell, 1(4), 28–39. 2006.

Ayrıntılar

Birincil Dil

İngilizce

Konular

Yapay Zeka

Bölüm

Araştırma Makalesi

Yayımlanma Tarihi

30 Haziran 2020

Gönderilme Tarihi

18 Aralık 2019

Kabul Tarihi

10 Mayıs 2020

Yayımlandığı Sayı

Yıl 2020 Cilt: 4 Sayı: 1

Kaynak Göster

APA
Alızada, B. (2020). Improved Whale Optimization Algorithm Based On π Number. International Scientific and Vocational Studies Journal, 4(1), 21-30. https://izlik.org/JA24KU96ET
AMA
1.Alızada B. Improved Whale Optimization Algorithm Based On π Number. ISVOS. 2020;4(1):21-30. https://izlik.org/JA24KU96ET
Chicago
Alızada, Bahadur. 2020. “Improved Whale Optimization Algorithm Based On π Number”. International Scientific and Vocational Studies Journal 4 (1): 21-30. https://izlik.org/JA24KU96ET.
EndNote
Alızada B (01 Haziran 2020) Improved Whale Optimization Algorithm Based On π Number. International Scientific and Vocational Studies Journal 4 1 21–30.
IEEE
[1]B. Alızada, “Improved Whale Optimization Algorithm Based On π Number”, ISVOS, c. 4, sy 1, ss. 21–30, Haz. 2020, [çevrimiçi]. Erişim adresi: https://izlik.org/JA24KU96ET
ISNAD
Alızada, Bahadur. “Improved Whale Optimization Algorithm Based On π Number”. International Scientific and Vocational Studies Journal 4/1 (01 Haziran 2020): 21-30. https://izlik.org/JA24KU96ET.
JAMA
1.Alızada B. Improved Whale Optimization Algorithm Based On π Number. ISVOS. 2020;4:21–30.
MLA
Alızada, Bahadur. “Improved Whale Optimization Algorithm Based On π Number”. International Scientific and Vocational Studies Journal, c. 4, sy 1, Haziran 2020, ss. 21-30, https://izlik.org/JA24KU96ET.
Vancouver
1.Bahadur Alızada. Improved Whale Optimization Algorithm Based On π Number. ISVOS [Internet]. 01 Haziran 2020;4(1):21-30. Erişim adresi: https://izlik.org/JA24KU96ET

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