A comparative study of population-based optimization algorithms for turning operations
Küçük Resim Yok
Tarih
2012
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Elsevier Science Inc
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In manufacturing industry, turning operations are used to remove unwanted sections of a part to obtain the final product. In this paper a comparison of state-of-the-art optimization techniques to solve multi-pass turning optimization problems is presented. Furthermore, a hybrid technique based on differential evolution algorithm is introduced for solving manufacturing optimization problems. The results have demonstrated the superiority of the hybrid approach over the other techniques like artificial bee colony algorithm, differential evolution algorithm, hybrid particle swarm optimization algorithm, hybrid artificial immune-hill climbing algorithm, hybrid taguchi-harmony search algorithm, hybrid robust genetic algorithm, scatter search algorithm, genetic algorithm and an improved simulated annealing algorithm in terms of convergence speed and efficiency by measuring the number of function evaluations required. (C) 2012 Elsevier Inc. All rights reserved.
Açıklama
Anahtar Kelimeler
Multi-pass turning, Differential evolution algorithm, Hybrid optimization
Kaynak
Information Sciences
WoS Q Değeri
Q1
Scopus Q Değeri
Q1
Cilt
210
