Optimum design of large-scale truss towers using cascade optimization

High number of design variables, large size of the search space, and control of a great number of design constraints are major preventive factors in performing optimum design of real-world structures in a reasonable time. The present study intends to examine the computational performance of cascadin...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Acta mechanica Jg. 227; H. 9; S. 2645 - 2656
Hauptverfasser: Kaveh, A., Ilchi Ghazaan, M.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Vienna Springer Vienna 01.09.2016
Springer
Springer Nature B.V
Schlagworte:
Algorithms
Cascades
Classical and Continuum Physics
Control
Convergence
Design
Design factors
Design optimization
Dynamical Systems
Engineering
Engineering Thermodynamics
Heat and Mass Transfer
Mathematical models
Mechanical engineering
Optimization
Original Paper
Solid Mechanics
Studies
Theoretical and Applied Mechanics
Towers
Trusses
Vibration
Harmony Search
Slenderness Ratio
Particle Swarm Optimization
Metaheuristic Algorithm
Design Variable
ISSN:0001-5970, 1619-6937
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:High number of design variables, large size of the search space, and control of a great number of design constraints are major preventive factors in performing optimum design of real-world structures in a reasonable time. The present study intends to examine the computational performance of cascading in design optimization of truss towers with large numbers of design variables. The cascade optimization procedure utilized in this paper reduces the objective function value over a number of optimization stages by initially operating on a small number of design variables, which is gradually increased stage after stage. In fact, the early stages of optimization in the cascade procedure make use of the coarsest configurations with small numbers of design variables and the later stages exploit finer configurations with larger numbers of design variables. The optimization algorithm utilized in each stage of a cascade process is enhanced colliding bodies optimization. High solution accuracy and convergence speed of the proposed method are shown through three test examples.
Bibliographie:SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 14
ObjectType-Article-1
ObjectType-Feature-2
content type line 23
ISSN:0001-5970
1619-6937
DOI:10.1007/s00707-016-1588-3