A Study of Joint Cost Inclusion in Linear Programming Optimization

The concept of Structural Optimization has been a topic or research over the past century. Linear Programming Optimization has proved being the most reliable method of structural optimization. Global advances in linear programming optimization have been recently powered by University of Sheffield re...

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Main Author: P. Armaos
Format: Article
Language:English
Published: D. G. Pylarinos 2013-08-01
Series:Engineering, Technology & Applied Science Research
Subjects:
Online Access:https://etasr.com/index.php/ETASR/article/view/327
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spelling doaj-bfc60810fc2e49ec944a6f02f25f6acd2020-12-02T15:08:47ZengD. G. PylarinosEngineering, Technology & Applied Science Research2241-44871792-80362013-08-0134A Study of Joint Cost Inclusion in Linear Programming OptimizationP. Armaos0Civil & Structural Engineer, MSc Steel Construction, GreeceThe concept of Structural Optimization has been a topic or research over the past century. Linear Programming Optimization has proved being the most reliable method of structural optimization. Global advances in linear programming optimization have been recently powered by University of Sheffield researchers, to include joint cost, self-weight and buckling considerations. A joint cost inclusion scopes to reduce the number of joints existing in an optimized structural solution, transforming it to a practically viable solution. The topic of the current paper is to investigate the effects of joint cost inclusion, as this is currently implemented in the optimization code. An extended literature review on this subject was conducted prior to familiarization with small scale optimization software. Using IntelliFORM software, a structured series of problems were set and analyzed. The joint cost tests examined benchmark problems and their consequent changes in the member topology, as the design domain was expanding. The findings of the analyses were remarkable and are being commented further on. The distinct topologies of solutions created by optimization processes are also recognized. Finally an alternative strategy of penalizing joints is presented. https://etasr.com/index.php/ETASR/article/view/327joint cost inclusionlinear programming optimizationstructural optimizationIntelliFORM
collection DOAJ
language English
format Article
sources DOAJ
author P. Armaos
spellingShingle P. Armaos
A Study of Joint Cost Inclusion in Linear Programming Optimization
Engineering, Technology & Applied Science Research
joint cost inclusion
linear programming optimization
structural optimization
IntelliFORM
author_facet P. Armaos
author_sort P. Armaos
title A Study of Joint Cost Inclusion in Linear Programming Optimization
title_short A Study of Joint Cost Inclusion in Linear Programming Optimization
title_full A Study of Joint Cost Inclusion in Linear Programming Optimization
title_fullStr A Study of Joint Cost Inclusion in Linear Programming Optimization
title_full_unstemmed A Study of Joint Cost Inclusion in Linear Programming Optimization
title_sort study of joint cost inclusion in linear programming optimization
publisher D. G. Pylarinos
series Engineering, Technology & Applied Science Research
issn 2241-4487
1792-8036
publishDate 2013-08-01
description The concept of Structural Optimization has been a topic or research over the past century. Linear Programming Optimization has proved being the most reliable method of structural optimization. Global advances in linear programming optimization have been recently powered by University of Sheffield researchers, to include joint cost, self-weight and buckling considerations. A joint cost inclusion scopes to reduce the number of joints existing in an optimized structural solution, transforming it to a practically viable solution. The topic of the current paper is to investigate the effects of joint cost inclusion, as this is currently implemented in the optimization code. An extended literature review on this subject was conducted prior to familiarization with small scale optimization software. Using IntelliFORM software, a structured series of problems were set and analyzed. The joint cost tests examined benchmark problems and their consequent changes in the member topology, as the design domain was expanding. The findings of the analyses were remarkable and are being commented further on. The distinct topologies of solutions created by optimization processes are also recognized. Finally an alternative strategy of penalizing joints is presented.
topic joint cost inclusion
linear programming optimization
structural optimization
IntelliFORM
url https://etasr.com/index.php/ETASR/article/view/327
work_keys_str_mv AT parmaos astudyofjointcostinclusioninlinearprogrammingoptimization
AT parmaos studyofjointcostinclusioninlinearprogrammingoptimization
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