Scopus
🔓 Açık Erişim YÖKSİS Eşleşti
A new ABC-based multiobjective optimization algorithm with an improvement approach (IBMO: Improved bee colony algorithm for multiobjective optimization)
Turkish Journal of Electrical Engineering and Computer Sciences · Ocak 2016
YÖKSİS Kayıtları
A new ABC based multiobjective optimization algorithm with an improvement approach IBMO improved bee colony algorithm for multiobjective optimization
TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES · 2016 SCI-Expanded
PROFESÖR MEHMET ÇUNKAŞ →
A new ABC-based multiobjective optimization algorithm with an improvement approach (IBMO: improved bee colony algorithm for multiobjective optimization)
TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES · 2016 SCI-Expanded
DOÇENT TAHİR SAĞ →
Makale Bilgileri
DergiTurkish Journal of Electrical Engineering and Computer Sciences
Yayın TarihiOcak 2016
Cilt / Sayfa24 · 2349-2373
Scopus ID2-s2.0-84974716031
Erişim🔓 Açık Erişim
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.
Yazarlar (2)
1
Tahir Saǧ
2
Mehmet Çunkaş
Anahtar Kelimeler
Artificial bee colony optimization
Evolutionary algorithm
Multiobjective optimization
Swarm intelligence
Kurumlar
Selçuk Üniversitesi
Selçuklu Turkey
Metrikler
7
Atıf
2
Yazar
4
Anahtar Kelime