Educated Reducing the effect of GA parameters on optimization of Topology and cross section for truss structures using Multi-Search Method

Although GA optimization is among optimization methods, the method may not be successfully employed in all cases due to slow down in process and some other unknown parameters including the number of generations, cross over ratio, mutation ratio, and the selection process which cause local optimized...

Full description

Bibliographic Details
Main Authors: M.H. Talebpour, V.R. Kalatjari
Format: Article
Language:fas
Published: Shahid Rajaee Teacher Training University (SRTTU) 2009-09-01
Series:Fanāvarī-i āmūzish
Subjects:
Online Access:https://jte.sru.ac.ir/article_1336_51c10fdc1a35d845f856dbc37ebbf00b.pdf
id doaj-e52816ce6ec944bdbd2528b88d243dac
record_format Article
spelling doaj-e52816ce6ec944bdbd2528b88d243dac2021-06-12T07:14:31ZfasShahid Rajaee Teacher Training University (SRTTU)Fanāvarī-i āmūzish2008-04412345-54622009-09-013429130610.22061/tej.2009.13361336Educated Reducing the effect of GA parameters on optimization of Topology and cross section for truss structures using Multi-Search MethodM.H. Talebpour0V.R. Kalatjari1Faculty of Civil Engineering and Architecture, Shahroud University of Technology, Semnan, IranFaculty of Civil Engineering and Architecture, Shahroud University of Technology, Semnan, IranAlthough GA optimization is among optimization methods, the method may not be successfully employed in all cases due to slow down in process and some other unknown parameters including the number of generations, cross over ratio, mutation ratio, and the selection process which cause local optimized points. In this paper a new approach is proposed to perform GA for optimization of cross section and topology of trusses that reduces such problems. A complete system with different sub sections, called island, is used to search in the design space. In each island, different operators and parameters are used separately. After some generations, depending on the migration ratio, the best chromosomes from each island alter the chromosomes with lower fitness in other island. Based on the proposed method, GA is continued until the global optimum with the least dependence on the GA parameters is achieved. The results were evaluated with some standard examples.https://jte.sru.ac.ir/article_1336_51c10fdc1a35d845f856dbc37ebbf00b.pdfcostinggenetic algorithmtruss structurestopologymultipurpose search method
collection DOAJ
language fas
format Article
sources DOAJ
author M.H. Talebpour
V.R. Kalatjari
spellingShingle M.H. Talebpour
V.R. Kalatjari
Educated Reducing the effect of GA parameters on optimization of Topology and cross section for truss structures using Multi-Search Method
Fanāvarī-i āmūzish
costing
genetic algorithm
truss structures
topology
multipurpose search method
author_facet M.H. Talebpour
V.R. Kalatjari
author_sort M.H. Talebpour
title Educated Reducing the effect of GA parameters on optimization of Topology and cross section for truss structures using Multi-Search Method
title_short Educated Reducing the effect of GA parameters on optimization of Topology and cross section for truss structures using Multi-Search Method
title_full Educated Reducing the effect of GA parameters on optimization of Topology and cross section for truss structures using Multi-Search Method
title_fullStr Educated Reducing the effect of GA parameters on optimization of Topology and cross section for truss structures using Multi-Search Method
title_full_unstemmed Educated Reducing the effect of GA parameters on optimization of Topology and cross section for truss structures using Multi-Search Method
title_sort educated reducing the effect of ga parameters on optimization of topology and cross section for truss structures using multi-search method
publisher Shahid Rajaee Teacher Training University (SRTTU)
series Fanāvarī-i āmūzish
issn 2008-0441
2345-5462
publishDate 2009-09-01
description Although GA optimization is among optimization methods, the method may not be successfully employed in all cases due to slow down in process and some other unknown parameters including the number of generations, cross over ratio, mutation ratio, and the selection process which cause local optimized points. In this paper a new approach is proposed to perform GA for optimization of cross section and topology of trusses that reduces such problems. A complete system with different sub sections, called island, is used to search in the design space. In each island, different operators and parameters are used separately. After some generations, depending on the migration ratio, the best chromosomes from each island alter the chromosomes with lower fitness in other island. Based on the proposed method, GA is continued until the global optimum with the least dependence on the GA parameters is achieved. The results were evaluated with some standard examples.
topic costing
genetic algorithm
truss structures
topology
multipurpose search method
url https://jte.sru.ac.ir/article_1336_51c10fdc1a35d845f856dbc37ebbf00b.pdf
work_keys_str_mv AT mhtalebpour educatedreducingtheeffectofgaparametersonoptimizationoftopologyandcrosssectionfortrussstructuresusingmultisearchmethod
AT vrkalatjari educatedreducingtheeffectofgaparametersonoptimizationoftopologyandcrosssectionfortrussstructuresusingmultisearchmethod
_version_ 1721380987499184128