The continuous artificial bee colony algorithm for binary optimization
Küçük Resim Yok
Tarih
2015
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
ELSEVIER
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Artificial bee colony (ABC) algorithm, one of the swarm intelligence algorithms, has been proposed for continuous optimization, inspired intelligent behaviors of real honey bee colony. For the optimization problems having binary structured solution space, the basic ABC algorithm should be modified because its basic version is proposed for solving continuous optimization problems. In this study, an adapted version of ABC, ABC(bin) for short, is proposed for binary optimization. In the proposed model for solving binary optimization problems, despite the fact that artificial agents in the algorithm works on the continuous solution space, the food source position obtained by the artificial agents is converted to binary values, before the objective function specific for the problem is evaluated. The accuracy and performance of the proposed approach have been examined on well-known 15 benchmark instances of uncapacitated facility location problem, and the results obtained by ABC(bin), are compared with the results of continuous particle swarm optimization (CPSO), binary particle swarm optimization (BPSO), improved binary particle swarm optimization (IBPSO), binary artificial bee colony algorithm (binABC) and discrete artificial bee colony algorithm (DisABC). The performance of ABC(bin) is also analyzed under the change of control parameter values. The experimental results and comparisons show that proposed ABC(bin) is an alternative and simple binary optimization tool in terms of solution quality and robustness. (C) 2015 Elsevier B.V. All rights reserved.
Açıklama
Anahtar Kelimeler
Artificial bee colony, Binary optimization, Conversion of continuous values, Uncapacitated facility location problem
Kaynak
APPLIED SOFT COMPUTING
WoS Q Değeri
Q1
Scopus Q Değeri
Q1
Cilt
33
