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TOSCA: a Tool for Optimisation in Structural and Civil engineering Analyses

Chisari, Corrado
•
Amadio, Claudio
2018
  • journal article

Periodico
INTERNATIONAL JOURNAL OF ADVANCED STRUCTURAL ENGINEERING
Abstract
Many structural engineering problems, e.g. parameter identification, optimal design and topology optimisation, involve the use of optimisation algorithms. Genetic algorithms (GA), in particular, have proved to be an effective framework for black-box problems and general enough to be applied to the most disparate problems of engineering practice. In this paper, the code TOSCA, which employs genetic algorithms in the search for the optimum, is described. It has been developed by the authors with the aim of providing a flexible tool for the solution of several optimisation problems arising in structural engineering. The interface has been developed to couple the programme to general solvers using text input/output files and in particular widely used finite element codes. The problem of GA parameter tuning is systematically dealt with by proposing some guidelines based on the role and behaviour of each operator. Two numerical applications are proposed to show how to assess the results and modify GA parameters accordingly, and to demonstrate the flexibility of the integrated approach proposed on a realistic case of seismic retrofitting optimal design.
DOI
10.1007/s40091-018-0205-1
Archivio
http://hdl.handle.net/11368/2934811
info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85057296040
https://link.springer.com/article/10.1007%2Fs40091-018-0205-1
Diritti
open access
license:creative commons
license uri:http://creativecommons.org/licenses/by/4.0/
FVG url
https://arts.units.it/bitstream/11368/2934811/2/Chisari-Amadio2018_Article_TOSCAAToolForOptimisationInStr.pdf
Soggetti
  • Genetic algorithm

  • Multi-objective optim...

  • Optimal design

  • Parameter tuning

  • Civil and Structural ...

Scopus© citazioni
8
Data di acquisizione
Jun 7, 2022
Vedi dettagli
Visualizzazioni
2
Data di acquisizione
Apr 19, 2024
Vedi dettagli
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