Optimum design of cold-formed steel channel beams using micro Genetic Algorithm

Jaehong Lee; Sun Myung Kim; Hyo Seon Park; Byung Hun Woo

doi:10.1016/j.engstruct.2004.08.008

Optimum design of cold-formed steel channel beams using micro Genetic Algorithm

Jaehong Lee, Sun Myung Kim, Hyo Seon Park, Byung Hun Woo

Department of Architecture and Architectural Engineering

Research output: Contribution to journal › Article › peer-review

70 Citations (Scopus)

Abstract

An important advantage of cold-formed steel is the great flexibility of cross-sectional profiles and sizes available to structural steel designers. However, this flexibility makes the selection of the most economical section difficult for a particular situation. In this study, a micro Genetic Algorithm (μ-GA) is used to find an optimum cross-section of cold-formed steel beams. The μ-GA is one of the improved form of GAs, to reduce iteration and computing resources by using small populations. The design curves are generated for optimum values of the thickness and the web flat-depth-to-thickness ratio for unbraced beams under uniformly distributed load. As numerical results, the optimum design curves are presented for various load level.

Original language	English
Pages (from-to)	17-24
Number of pages	8
Journal	Engineering Structures
Volume	27
Issue number	1
DOIs	https://doi.org/10.1016/j.engstruct.2004.08.008
Publication status	Published - 2005 Jan

Bibliographical note

Funding Information:
The first author would like to express his gratitude for the financial support by the Korea Institute of Industrial Technology Evaluation and Planning through Grant 10002825.

All Science Journal Classification (ASJC) codes

Civil and Structural Engineering

Access to Document

10.1016/j.engstruct.2004.08.008

Cite this

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title = "Optimum design of cold-formed steel channel beams using micro Genetic Algorithm",

abstract = "An important advantage of cold-formed steel is the great flexibility of cross-sectional profiles and sizes available to structural steel designers. However, this flexibility makes the selection of the most economical section difficult for a particular situation. In this study, a micro Genetic Algorithm (μ-GA) is used to find an optimum cross-section of cold-formed steel beams. The μ-GA is one of the improved form of GAs, to reduce iteration and computing resources by using small populations. The design curves are generated for optimum values of the thickness and the web flat-depth-to-thickness ratio for unbraced beams under uniformly distributed load. As numerical results, the optimum design curves are presented for various load level.",

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AU - Lee, Jaehong

AU - Kim, Sun Myung

AU - Park, Hyo Seon

AU - Woo, Byung Hun

N1 - Funding Information: The first author would like to express his gratitude for the financial support by the Korea Institute of Industrial Technology Evaluation and Planning through Grant 10002825.

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AB - An important advantage of cold-formed steel is the great flexibility of cross-sectional profiles and sizes available to structural steel designers. However, this flexibility makes the selection of the most economical section difficult for a particular situation. In this study, a micro Genetic Algorithm (μ-GA) is used to find an optimum cross-section of cold-formed steel beams. The μ-GA is one of the improved form of GAs, to reduce iteration and computing resources by using small populations. The design curves are generated for optimum values of the thickness and the web flat-depth-to-thickness ratio for unbraced beams under uniformly distributed load. As numerical results, the optimum design curves are presented for various load level.

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Optimum design of cold-formed steel channel beams using micro Genetic Algorithm

Abstract

Bibliographical note

All Science Journal Classification (ASJC) codes

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