Performance comparison of metaheuristic algorithms for the optimal design of space trusses
Yükleniyor...
Tarih
2018
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Springer Heidelberg
Erişim Hakkı
info:eu-repo/semantics/embargoedAccess
Özet
In this study, eight population-based metaheuristic algorithms were employed for the design of truss structures with continuous design variables. The selected algorithms were genetic, ant colony, particle swarm, artificial bee colony, gravitational search, firefly, gray wolf optimization and Jaya. The purpose was to objectively evaluate the performance of these algorithms under the same conditions and select the best efficient algorithm by assessing three example truss structures. The results obtained from the examples showed that the algorithms were both computationally efficient and robust when the number of design variables was approximately 10 and a significant number of iterations were performed. When the number of design variables was increased to 53, artificial bee colony, Jaya and gray wolf optimization were found to be computationally more effective than the remaining algorithms.
Açıklama
Anahtar Kelimeler
Genetic Algorithm, Ant Colony Optimization, Artificial Bee Colony, Gray Wolf Optimization, Firefly Algorithms, Gravitational Search Algorithm, Jaya
Kaynak
Arabian Journal For Science and Engineering
WoS Q Değeri
N/A
Scopus Q Değeri
Q1
Cilt
43
Sayı
10
