Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
Ant Colony Search Method in Practical Structural Optimization
Date
2011-06-01
Author
Hasançebi, Oğuzhan
Metadata
Show full item record
Item Usage Stats
202
views
0
downloads
Cite This
This paper is concerned with application and evaluation of ant colony optimization (ACO) method to practical structural optimization problems. In particular, a size optimum design of pin-jointed truss structures is considered with ACO such that the members are chosen from ready sections for minimum weight design. The application of the algorithm is demonstrated using two design examples with practical design considerations. Both examples are formulated according to provisions of ASD-AISC (Allowable Stress Design Code of American Institute of Steel Institution) specification. The results obtained are used to discuss the computational characteristics of ACO for optimum design of truss type structures.
Subject Keywords
Ant colony optimization
,
Stochastic search techniques
,
Discrete optimum
,
Steel truss structures
,
Minimum weight design
URI
https://hdl.handle.net/11511/76949
http://ijoce.iust.ac.ir/article-1-9-en.html
Journal
International Journal of Optimization in Civil Engineering
Collections
Department of Civil Engineering, Article
Suggestions
OpenMETU
Core
A reformulation of the ant colony optimization algorithm for large scale structural optimization
Hasançebi, Oğuzhan; Saka, M.p. (2011-01-01)
This study intends to improve performance of ant colony optimization (ACO) method for structural optimization problems particularly with many design variables or when design variables are chosen from large discrete sets. The algorithm developed with ACO method employs the so-called pheromone scaling approach to overcome entrapment of the search in a poor local optimum and thus to recover efficiency of the method for large-scale optimization problems. Besides, a new formulation is proposed for the local upda...
Adaptive evolution strategies in structural optimization: Enhancing their computational performance with applications to large-scale structures
Hasançebi, Oğuzhan (2008-01-01)
In this study the computational performance of adaptive evolution strategies (ESs) in large-scale structural optimization is mainly investigated to achieve the following objectives: (i) to present an ESs based solution algorithm for efficient optimum design of large structural systems consisting of continuous, discrete and mixed design variables; (ii) to integrate new parameters and methodologies into adaptive ESs to improve the computational performance of the algorithm; and (iii) to assess successful self...
Discrete sizing optimization of steel trusses under multiple displacement constraints and load cases using guided stochastic search technique
Azad, S. Kazemzadeh; Hasançebi, Oğuzhan (2015-08-01)
The guided stochastic search (GSS) is a computationally efficient design optimization technique, which is originally developed for discrete sizing optimization problems of steel trusses with a single displacement constraint under a single load case. The present study aims to investigate the GSS in a more general class of truss sizing optimization problems subject to multiple displacement constraints and load cases. To this end, enhancements of the GSS are proposed in the form of two alternative approaches t...
Upper Bound Strategy in Optimum Design of Truss Structures: A Big Bang-Big Crunch Algorithm Based Application
Kazemzadeh Azad, Saeid; Hasançebi, Oğuzhan; Kazemzadeh Azad, Sina; Erol, Osman Kaan (2013-06-01)
One main shortcoming of metaheuristic search techniques in structural optimization is the large number of time-consuming structural analyses required for convergence to a reasonable solution. This study is an attempt to apply the so-called upper bound strategy (UBS) as a simple, yet an efficient strategy to reduce the total number of structural analyses through avoiding unnecessary analyses during the course of optimization. Although, the usefulness of the UBS is demonstrated in conjunction with a big bang-...
Optimum Design of Geodesic Steel Domes Under Code Provisions using Metaheuristic Techniques
Hasançebi, Oğuzhan; Saka, Mehmet Polat (2010-06-01)
Metaheuristic search techniques strongly employ randomized decisions while searching for solutions to structural optimization problems. These techniques play an increasingly important role for practically solving hard combinatorial problems from various domains. Over the past few years there has been considerable success in developing metaheuristic search algorithms as well as randomized systematic search methods for obtaining solutions to discrete programming problems. This paper examines minimum weight de...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
O. Hasançebi, “Ant Colony Search Method in Practical Structural Optimization,”
International Journal of Optimization in Civil Engineering
, pp. 91–105, 2011, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/76949.