Metaheuristic optimization in structural engineering

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Tarih

2016

Dergi Başlığı

Dergi ISSN

Cilt Başlığı

Yayıncı

Springer International Publishing Ag

Erişim Hakkı

info:eu-repo/semantics/closedAccess

Özet

Metaheuristic search methods have been extensively used for optimization of the structures over the past two decades. Genetic algorithms (GA), ant colony optimization (ACO), particle swarm optimization (PSO), harmony search (HS), big bang-big crunch (BB-BC), artificial bee colony algorithm (ABC) and teaching-learning-based optimization (TLBO) are the most popular metaheuristic optimization methods. The basic principle of these methods is that they make an analogy between the natural phenomena and the optimization problems. In this chapter, recently developed metaheuristic optimization methods such as self-adaptive harmony search and teaching-learning-based optimization are reviewed and the performance of these methods in the field of structural engineering are compared with each other and the other metaheuristic methods.

Açıklama

Anahtar Kelimeler

Metaheuristic optimization, Structural engineering, Truss structures

Kaynak

Metaheuristics and Optimization in Civil Engineering

WoS Q Değeri

N/A

Scopus Q Değeri

N/A

Cilt

7

Sayı

Künye

Değertekin, S.Ö. ve Geem, Z.W. (2016). Metaheuristic optimization in structural engineering. Modeling and Optimization in Science and Technologies içinde, 7, pp. 75–93