Improved binary artificial bee colony algorithm
Küçük Resim Yok
Tarih
2021
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Zhejiang Univ
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
The artificial bee colony (ABC) algorithm is an evolutionary optimization algorithm based on swarm intelligence and inspired by the honey bees' food search behavior. Since the ABC algorithm has been developed to achieve optimal solutions by searching in the continuous search space, modification is required to apply it to binary optimization problems. In this study, we modify the ABC algorithm to solve binary optimization problems and name it the improved binary ABC (IbinABC). The proposed method consists of an update mechanism based on fitness values and the selection of different decision variables. Therefore, we aim to prevent the ABC algorithm from getting stuck in a local minimum by increasing its exploration ability. We compare the IbinABC algorithm with three variants of the ABC and other meta-heuristic algorithms in the literature. For comparison, we use the well-known OR-Library dataset containing 15 problem instances prepared for the uncapacitated facility location problem. Computational results show that the proposed algorithm is superior to the others in terms of convergence speed and robustness. The source code of the algorithm is available at .
Açıklama
Anahtar Kelimeler
Artificial bee colony, Binary optimization, Uncapacitated facility location problem (UFLP), TP301, 6
Kaynak
Frontiers of Information Technology & Electronic Engineering
WoS Q Değeri
Q2
Scopus Q Değeri
Q2
Cilt
22
Sayı
8
