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research article

MILP-based discrete sizing and topology optimization of truss structures: new formulation and benchmarking

Brutting, Jan  
•
Senatore, Gennaro  
•
Fivet, Corentin  
October 1, 2022
Structural And Multidisciplinary Optimization

Discrete sizing and topology optimization of truss structures subject to stress and displacement constraints has been formulated as a Mixed-Integer Linear Programming (MILP) problem. The computation time to solve a MILP problem to global optimality via a branch-and-cut solver highly depends on the problem size, the choice of design variables, and the quality of optimization constraint formulations. This paper presents a new formulation for discrete sizing and topology optimization of truss structures, which is benchmarked against two well-known existing formulations. Benchmarking is carried out through case studies to evaluate the influence of the number of structural members, candidate cross sections, load cases, and design constraints (e.g., stress and displacement limits) on computational performance. Results show that one of the existing formulations performs significantly worse than all other formulations. In most cases, the new formulation proposed in this work performs best to obtain near-optimal solutions and verify global optimality in the shortest computation time.

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Type
research article
DOI
10.1007/s00158-022-03325-7
Web of Science ID

WOS:000854859700003

Author(s)
Brutting, Jan  
Senatore, Gennaro  
Fivet, Corentin  
Date Issued

2022-10-01

Published in
Structural And Multidisciplinary Optimization
Volume

65

Issue

10

Start page

277

Subjects

Computer Science, Interdisciplinary Applications

•

Engineering, Multidisciplinary

•

Mechanics

•

Computer Science

•

Engineering

•

structural optimization

•

truss

•

sizing optimization

•

topology optimization

•

mixed-integer linear programming

•

gurobi

•

optimal-design

•

branch

•

scale

•

variables

•

shape

URL

Correction to

https://link.springer.com/article/10.1007/s00158-022-03452-1
Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
IMAC  
SXL  
Available on Infoscience
September 26, 2022
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/190917
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