İstatistiksel Olarak Yönlendirilen Yapay Arı Kolonisi Algoritması
Yapay Arı Koloni algoritması, doğadan ilham alan meta sezgisel yöntemlerinden biridir. Metasezgisel yöntemle, daha iyi sonuçlar elde etmek için akla ilk gelen çözüm hesaplama süresini arttırmakveya uygunluk hesaplama sayısını arttırmaktır. Ancak istenilen yol, daha az hesaplama ile daha iyisonuçlar elde etmektir. Bu çalışmada, istatistiksel gözlemlerden yararlanarak, aynı uygunluk hesaplamasayısı ile daha iyi sonuçlar bulunabilen Yapay Arı Koloni Algoritması, geliştirilmiştir.
STATISTICALLY GUIDED ARTIFICIAL BEE COLONY ALGORITHM
Artificial Bee Colony algorithm is one of the naturally inspired meta heuristic method. Asusual, in a meta heuristic method, intuitively appealing way to have better results is extendingcalculation time or increasing the fitness evaluation count. But the desired way is acquiring better resultswith less computation. So in this work a modified Artificial Bee Colony algorithm which can find betterresults with same computation is developed by benefiting statistical observations.
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- Akay, B., Karaboga, D., 2012 “A Modified Artificial Bee Colony Algorithm for Real-Parameter
Optimization”, Information Sciences, Vol. 192, pp. 120-142. doi:10.1016/j.ins.2010.07.015
- Basturk, B., Karaboga, D., “An Artificial Bee Colony (ABC) Algorithm for Numeric Function
Optimization”, IEEE Swarm Intelligence Symposium, Indianapolis, Indiana, USA, May 2006.
- Dorigo, M., Maniezzo, V., Colorni, A., Positive Feedback as a Search Strategy, Technical Report 91-016,
Politecnico di Milano, Italy, 1991.
- Drias, H., Sadeg, S., Yahi, S., “Cooperative Bees Swarm for solving The Maximum Weighted
Satisfiability Problem”, Computational Intelligence and Bioinspired Systems. in: 8th
International Workshop on Artificial Neural Networks IWANN 2005, Vilanova, Barcelona,
Spain, June 8–10 2005.
- Holland, J.H., 1975, Adaptation in Natural and Artificial Systems, University of Michigan Press, Ann
Arbor, MI.
- Karaboga, D., 2005, An Idea Based on Honeybee Swarm for Numerical Optimization, Technical Report
TR06, Erciyes University, Engineering Faculty, Computer Engineering Department.
- Karaboga, D., Basturk, B., 2007, “A Powerful and Efficient Algorithm for Numerical Function
Optimization: Artificial Bee Colony (ABC) algorithm”, Journal of Global Optimization, Vol. 39
(3), pp. 459–471.
- Karaboga, D., Akay, B., “Solving Large Scale Numerical Problems Using Artificial Bee Colony
Algorithm”, in: Sixth International Symposium on Intelligent and Manufacturing Systems
Features, Strategies and Innovation, Sakarya, Türkiye, 14–17 October 2008.
- Karaboga, D., Akay, B., “An Artificial Bee Colony (ABC) Algorithm on Training Artificial Neural
Networks”, in: 15th IEEE Signal Processing and Communications Applications, SIU 2007,
Eskisehir, Türkiye, pp. 1–4, June 2007.
- Karaboga, D., Basturk, B., 2008, “On The Performance of Artificial Bee Colony (ABC) Algorithm”,
Applied Soft Computing, Vol. 8 (1), pp. 687–697.
- Karaboga, D., Akay, B., Ozturk, C., 2007, “Modeling Decisions for Artificial Intelligence, Artificial Bee
Colony (ABC) Optimization Algorithm for Training Feed-Forward Neural Networks”, LNCS
4617/2007, Springer-Verlag, pp. 318–329.
- Karaboga, D., Ozturk, C., Akay, B., “Training Neural Networks with ABC Optimization Algorithm on
Medical Pattern Classification”, in: International Conference on Multivariate Statistical
Modelling and High Dimensional Data Mining, Kayseri, TURKEY, 19–23 June 2008.
- Kennedy, J., Eberhart, R.C., in: “Particle Swarm Optimization”, 1995 IEEE International Conference on
Neural Networks, Vol. 4, pp. 1942–1948, 1995.
- Lucic, P., Teodorovic´, D., “Transportation Modeling: An Artificial Life Approach”, 14th IEEE
International Conference on Tools with Artificial Intelligence ( ICTAI, 2002), pp. 216–223, 4-6
November 2002.
- Ozturk, C., Karaboga, D., “Classification by Neural Networks and Clustering with Artificial Bee Colony
(ABC) Algorithm”, in: Sixth International Symposium on Intelligent and Manufacturing
Systems Features, Strategies and Innovation, Sakarya, Türkiye, 14–17 October 2008.
- Shrivastava A., Gupta M., Swami S., “Enhanced Artificial Bee Colony Algorithm with SPV for Travelling
Salesman Problem”, 2015 International Conference on Computing Communication Control
and Automation, Pune, pp. 887-891, 2015.
- Teodorovic´, D., 2003, “Transport Modeling by Multi-Agent Systems: a Swarm Intelligence Approach”,
Transportation Planning and Technology, Vol. 26 (4), pp. 289-312.
- Yang, X.S., “Engineering Optimizations via Nature-inspired Virtual Bee Algorithms”, in: Artificial
Intelligence and Knowledge Engineering Applications: A Bioinspired Approach, LNCS, vol.
3562/2005, pp. 317– 323, June 2005.