On the performance of a modified multiple-deme genetic algorithm in LRFD design of steel frames

D. Safari, Mahmoud R. Maheri, Alireza Maheri

Research output: Contribution to journalArticle

9 Citations (Scopus)

Abstract

This paper investigates the performance of a multiple-deme genetic algorithm (GA) with modified reproduction operators, in optimal design of planar steel frames according to the AISC-LRFD specification. The design objective is to minimise the weight of frame subject to strength, displacement and constructability constraints. A number of new crossover and mutation operators, used alongside the standard operators are utilised in optimum design of a number of steel frames subjected to the constraints of the AISC-LRFD specification, with and without considering the second order effects, as set out by the code requirements. This modified GA (MGA) is shown to have a very fast convergence and to produce relatively high-quality designs. This paper also utilizes the concept of multiple-deme in the GA, as it has been used successfully for other metaheuristic population-based methods. The multiple-deme GA is used alongside the modified GA operators and the algorithm is named the modified multiple-deme GA (MMDGA). The modified GA (MGA) and modified multiple-deme GA (MMDGA) are applied to three benchmark problems and the results are compared to those obtained by other metaheuristic methods. In the majority of cases, the results of comparisons suggest the superiority of the MMDGA in terms of the quality of final design and the total number of performed finite elements analyses
Original languageEnglish
Pages (from-to)169-190
Number of pages21
JournalIranian Journal of Science and Technology:Transactions of Civil Engineering
Volume37
Issue number2
DOIs
Publication statusPublished - 2013

Fingerprint

genetic algorithm
Genetic algorithms
steel
Steel
Mathematical operators
Specifications
mutation

Keywords

  • Optimum design
  • multiple-deme genetic algorithm
  • steel frames
  • AISC-LRFD

Cite this

On the performance of a modified multiple-deme genetic algorithm in LRFD design of steel frames. / Safari, D.; Maheri, Mahmoud R.; Maheri, Alireza.

In: Iranian Journal of Science and Technology:Transactions of Civil Engineering, Vol. 37, No. 2, 2013, p. 169-190.

Research output: Contribution to journalArticle

@article{59924f0504ed45548fc439853ad3cde0,
title = "On the performance of a modified multiple-deme genetic algorithm in LRFD design of steel frames",
abstract = "This paper investigates the performance of a multiple-deme genetic algorithm (GA) with modified reproduction operators, in optimal design of planar steel frames according to the AISC-LRFD specification. The design objective is to minimise the weight of frame subject to strength, displacement and constructability constraints. A number of new crossover and mutation operators, used alongside the standard operators are utilised in optimum design of a number of steel frames subjected to the constraints of the AISC-LRFD specification, with and without considering the second order effects, as set out by the code requirements. This modified GA (MGA) is shown to have a very fast convergence and to produce relatively high-quality designs. This paper also utilizes the concept of multiple-deme in the GA, as it has been used successfully for other metaheuristic population-based methods. The multiple-deme GA is used alongside the modified GA operators and the algorithm is named the modified multiple-deme GA (MMDGA). The modified GA (MGA) and modified multiple-deme GA (MMDGA) are applied to three benchmark problems and the results are compared to those obtained by other metaheuristic methods. In the majority of cases, the results of comparisons suggest the superiority of the MMDGA in terms of the quality of final design and the total number of performed finite elements analyses",
keywords = "Optimum design, multiple-deme genetic algorithm, steel frames, AISC-LRFD",
author = "D. Safari and Maheri, {Mahmoud R.} and Alireza Maheri",
year = "2013",
doi = "10.22099/IJSTC.2013.1610",
language = "English",
volume = "37",
pages = "169--190",
journal = "Iranian Journal of Science and Technology:Transactions of Civil Engineering",
issn = "2228-6160",
publisher = "Shiraz University",
number = "2",

}

TY - JOUR

T1 - On the performance of a modified multiple-deme genetic algorithm in LRFD design of steel frames

AU - Safari, D.

AU - Maheri, Mahmoud R.

AU - Maheri, Alireza

PY - 2013

Y1 - 2013

N2 - This paper investigates the performance of a multiple-deme genetic algorithm (GA) with modified reproduction operators, in optimal design of planar steel frames according to the AISC-LRFD specification. The design objective is to minimise the weight of frame subject to strength, displacement and constructability constraints. A number of new crossover and mutation operators, used alongside the standard operators are utilised in optimum design of a number of steel frames subjected to the constraints of the AISC-LRFD specification, with and without considering the second order effects, as set out by the code requirements. This modified GA (MGA) is shown to have a very fast convergence and to produce relatively high-quality designs. This paper also utilizes the concept of multiple-deme in the GA, as it has been used successfully for other metaheuristic population-based methods. The multiple-deme GA is used alongside the modified GA operators and the algorithm is named the modified multiple-deme GA (MMDGA). The modified GA (MGA) and modified multiple-deme GA (MMDGA) are applied to three benchmark problems and the results are compared to those obtained by other metaheuristic methods. In the majority of cases, the results of comparisons suggest the superiority of the MMDGA in terms of the quality of final design and the total number of performed finite elements analyses

AB - This paper investigates the performance of a multiple-deme genetic algorithm (GA) with modified reproduction operators, in optimal design of planar steel frames according to the AISC-LRFD specification. The design objective is to minimise the weight of frame subject to strength, displacement and constructability constraints. A number of new crossover and mutation operators, used alongside the standard operators are utilised in optimum design of a number of steel frames subjected to the constraints of the AISC-LRFD specification, with and without considering the second order effects, as set out by the code requirements. This modified GA (MGA) is shown to have a very fast convergence and to produce relatively high-quality designs. This paper also utilizes the concept of multiple-deme in the GA, as it has been used successfully for other metaheuristic population-based methods. The multiple-deme GA is used alongside the modified GA operators and the algorithm is named the modified multiple-deme GA (MMDGA). The modified GA (MGA) and modified multiple-deme GA (MMDGA) are applied to three benchmark problems and the results are compared to those obtained by other metaheuristic methods. In the majority of cases, the results of comparisons suggest the superiority of the MMDGA in terms of the quality of final design and the total number of performed finite elements analyses

KW - Optimum design

KW - multiple-deme genetic algorithm

KW - steel frames

KW - AISC-LRFD

U2 - 10.22099/IJSTC.2013.1610

DO - 10.22099/IJSTC.2013.1610

M3 - Article

VL - 37

SP - 169

EP - 190

JO - Iranian Journal of Science and Technology:Transactions of Civil Engineering

JF - Iranian Journal of Science and Technology:Transactions of Civil Engineering

SN - 2228-6160

IS - 2

ER -