KaydedilenlerDerginizi ekleyin

Dergiler / Sakarya University Journal of Science / 2022 / Cilt: 26 Sayı: 6

Investigation of The Effect of Feeding Period in Honey Bee Algorithm

Mustafa KAYA
Sayfa
1071–1083
Yayın Tarihi
2022-12-31
DOI
—
🏛️Bu makalenin bibliyografik verileri ve tam metin bağlantısı DergiPark üzerinden sağlanmıştır.
DergiPark Kaydı ↗
✨

Yapay Zeka Hızlı Bakış & Çıkarımlar

AI Insight
⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

As a result, the analysis results showed that the performance of the artificial bee colony algorithm is very good while solving too complex engineering optimization problems.

📌 3 Maddede Bu Makale

🎯
Amaç & Hipotez:In the study, it was investigated the ejaculation ability and semen quality of drones, according to feeding with pollen in different periods.
📊
Temel Bulgular & Veri:In the first step of the study, 16 %, 32 %, 47 %, 63 %, 79 %, and 100 % feeding periods were applied to the drones, for investigating the effect on ejaculation ability, and the semen quality of drones was investigated.
💡
Sonuç & Katkı:As a result, the analysis results showed that the performance of the artificial bee colony algorithm is very good while solving too complex engineering optimization problems.
🔬Tür:Modelleme & Sayısal Simülasyon
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Bee colony algorithm · feding period effect · knapsack problems

Abstract

In the study, it was investigated the ejaculation ability and semen quality of drones, according to feeding with pollen in different periods. In the first step of the study, 16 %, 32 %, 47 %, 63 %, 79 %, and 100 % feeding periods were applied to the drones, for investigating the effect on ejaculation ability, and the semen quality of drones was investigated. While investigating these feeding period effects “0-1”, bonded, and unbounded knapsack optimization problems were used. After the most effective feeding period was determined, this period was applied to the traveling salesman and liquid storage tank problems in the second step of the study. In the analysis of the traveling salesman problem, it was determined the shortest way between two cities. Analysis of the liquid storage tank problem, it was determined the minimum connector areas. As a result, the analysis results showed that the performance of the artificial bee colony algorithm is very good while solving too complex engineering optimization problems.

🔖

Bu Makaleye Atıf Yap

KAYA, M. (2022). Investigation of The Effect of Feeding Period in Honey Bee Algorithm. Sakarya University Journal of Science, Cilt: 26 Sayı: 6, 1071–1083. https://ajindex.com/articles/941677

📄 Tam Metin PDF Okuyucu

📄

PDF görüntüleyici hazırlanıyor...

Kaynakça (12)

  1. D. Pham, A. Ghanbarzadeh, E. Koc, S. Otri, S. Rahim, M. Zaidi, “The Bees Algorithm A Novel Tool For Complex Optimization Problems”, Proceedings of the 2nd Virtual International Conference on Intelligent Production Machines and Systems (EPROMS 2006). Elsevier Science Ltd, Cardiff, UK, 2006
  2. D. Pham, A. Ghanbarzadeh, “Multiobjective Optimization Using The Bees Algorithm”, 3rd International Virtual Conference on Intelligent Production Machines and Systems (EPROMS 2007), Whittles, Dunbeath, Scotland, pp. 111-116, 2007
  3. B. Yuce, D. Pham D, M. Packianather, E. Mastrocinque, “An Enhancement To The Bees Algorithm With Slope Angle Computation And Hill Climbing Algorithm And Its Applications In Scheduling And Continuous Type Optimization Problem”, Production & Manufacturing Research, vol. 3, pp. 3-19, 2015
  4. S. Abdullah, M. Alzaqebah, “A hybrid Self Adaptive Bees Algorithm For Examination Timetabling Problems”, Applied Soft Computing, vol. 13, pp. 3608-3620, 2013
  5. C. Lara, JJ. Flores, F. Calderón, “Solving A School Timetabling Problem Using A Bee Algorithm”, Advances in Artificial Intelligence. Springer, Berlin, Heidelberg, 2008
  6. Z. Dongli, G. Xinping, T. Yinggan, T. Yong, “Modified Artificial Bee Colony Algorithms for Numerical Optimization”, in Proc. 3rd International Workshop on Intelligent Systems and Applications, 2011, pp. 1–4, 2011
  7. A. Banharnsakun, T. Achalakul and B. Sirinaovakul B, “The best-so-far selection in Artificial Bee Colony algorithm”, Applied Soft Computing, Vol. 11, no. 2, pp. 2888-2901, 2011
  8. S. Anusara, A. Selamatab R. Sallehuddin, “A modified scout bee for artificial bee colony algorithm and its performance on optimization problems”, Journal of King Saud University - Computer and Information Sciences, vol 28, no. 4, pp. Pages 395-406, 2016
  9. I. Brajevic, M. Tuba, “An upgraded artificial bee colony (ABC) algorithm for constrained optimization problems”, manufacturing, vol. 24, pp. 729–740, 2013
  10. K. Diwold, A. Andrej, A. Scheidler, “Middendorf M, Performance evaluation of artificial bee colony optimization and new selection schemes”, Memetic Computing, vol. 3, pp. 149-162, 2011
  11. E. Cuevas, F. Sención, D. Zaldivar, M. Pérez-Cisneros and H. Sossa, “A multi-threshold segmentation approach based on Artificial Bee Colony optimization”, Applied Intelligence, vol. 37, pp. 321–336, 2012
  12. PW. Tsai, JS. Pan, BY. Liao, SC. Chu (2009), “Enhanced Artificial Bee Colony Optimization”, International Journal of I