A new ABC-based multiobjective optimization algorithm with an improvement approach (IBMO: improved bee colony algorithm for multiobjective optimization)
Küçük Resim Yok
Tarih
2016
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
TUBITAK SCIENTIFIC & TECHNICAL RESEARCH COUNCIL TURKEY
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
This paper presents a new metaheuristic algorithm based on the artificial bee colony (ABC) algorithm for multiobjective optimization problems. The proposed hybrid algorithm, an improved bee colony algorithm for multiobjective optimization called IBMO, combines the main ideas of the simple ABC with nondominated sorting strategy corresponding to the principal framework of multiobjective optimization such as Pareto-dominance and crowding distance. A fixed-sized external archive to store the nondominated solutions and an improvement procedure to promote the convergence to true Pareto front are used. The presented approach, IBMO, is compared with four representatives of the state-of-the-art algorithms: NSGA2, SPEA2, OMOPSO, and AbYSS. IBMO and the selected algorithms from specialized literature are applied to several multiobjective benchmark functions by considering the number of function evaluations. Then four quality indicators are employed for performance evaluations: general distance, spread, maximum spread, and hypervolume. The results show that the IBMO is superior to the other methods.
Açıklama
Anahtar Kelimeler
Multiobjective optimization, artificial bee colony optimization, evolutionary algorithm, swarm intelligence
Kaynak
TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES
WoS Q Değeri
Q4
Scopus Q Değeri
Q3
Cilt
24
Sayı
4
