A study for efficiently solving optimisation problems with an increasing number of design variables

S. Trichon; M.H.A. Bonte; A.H. van den Boogaard; J.-P. Ponthot

doi:10.1063/1.2740857

A study for efficiently solving optimisation problems with an increasing number of design variables

S. Trichon
, M.H.A. Bonte
, A.H. van den Boogaard
, J.-P. Ponthot

Faculty of Engineering Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

1 Citation (Scopus)

11 Downloads (Pure)

Abstract

Coupling optimisation algorithms to Finite Element Methods (FEM) is a very promising way to achieve optimal metal forming processes. However, many optimisation algorithms exist and it is not clear which of these algorithms to use. This paper investigates the sensitivity of a Sequential Approximate Optimisation algorithm (SAO) proposed in [1–4] to an increasing number of design variables and compares it with two other algorithms: an Evolutionary Strategy (ES) and an Evolutionary version of the SAO (ESAO). In addition, it observes the influence of different Designs Of Experiments used with the SAO. It is concluded that the SAO is very capable and efficient and its combination with an ES is not beneficial. Moreover, the use of SAO with Fractional Factorial Design is the most efficient method, rather than Full Factorial Design as proposed in [1–4].

Original language	English
Title of host publication	Materials processing and design: modeling, simulation and applications
Subtitle of host publication	NUMIFORM '07 : proceedings of the 9th International Conference on Numerical Methods in Industrial Forming Processes, Porto, Portugal, 17-21 June, 2007
Editors	J.M.A. César de Sá, Abel D. Santos
Place of Publication	Melville, NY
Publisher	American Institute of Physics
Pages	481-486
ISBN (Electronic)	978-0-7354-0416-8
ISBN (Print)	978-0-7354-0415-1
DOIs	https://doi.org/10.1063/1.2740857
Publication status	Published - 2007
Event	9th International Conference on Numerical Methods in Industrial Forming Processes, NUMIFORM 2007 - Porto, Portugal Duration: 17 Jun 2007 → 21 Jun 2007 Conference number: 9

Conference

Conference	9th International Conference on Numerical Methods in Industrial Forming Processes, NUMIFORM 2007
Abbreviated title	NUMIFORM
Country/Territory	Portugal
City	Porto
Period	17/06/07 → 21/06/07

Keywords

Metamodelling
Design of Experiments (DoE)
Numerical optimisation

Access to Document

10.1063/1.2740857

Cite this

Trichon, S., Bonte, M. H. A., van den Boogaard, A. H., & Ponthot, J.-P. (2007). A study for efficiently solving optimisation problems with an increasing number of design variables. In J. M. A. César de Sá, & A. D. Santos (Eds.), Materials processing and design: modeling, simulation and applications: NUMIFORM '07 : proceedings of the 9th International Conference on Numerical Methods in Industrial Forming Processes, Porto, Portugal, 17-21 June, 2007 (pp. 481-486). American Institute of Physics. https://doi.org/10.1063/1.2740857

Trichon, S. ; Bonte, M.H.A. ; van den Boogaard, A.H. et al. / A study for efficiently solving optimisation problems with an increasing number of design variables. Materials processing and design: modeling, simulation and applications: NUMIFORM '07 : proceedings of the 9th International Conference on Numerical Methods in Industrial Forming Processes, Porto, Portugal, 17-21 June, 2007. editor / J.M.A. César de Sá ; Abel D. Santos. Melville, NY : American Institute of Physics, 2007. pp. 481-486

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title = "A study for efficiently solving optimisation problems with an increasing number of design variables",

abstract = "Coupling optimisation algorithms to Finite Element Methods (FEM) is a very promising way to achieve optimal metal forming processes. However, many optimisation algorithms exist and it is not clear which of these algorithms to use. This paper investigates the sensitivity of a Sequential Approximate Optimisation algorithm (SAO) proposed in [1–4] to an increasing number of design variables and compares it with two other algorithms: an Evolutionary Strategy (ES) and an Evolutionary version of the SAO (ESAO). In addition, it observes the influence of different Designs Of Experiments used with the SAO. It is concluded that the SAO is very capable and efficient and its combination with an ES is not beneficial. Moreover, the use of SAO with Fractional Factorial Design is the most efficient method, rather than Full Factorial Design as proposed in [1–4].",

keywords = "Metamodelling, Design of Experiments (DoE), Numerical optimisation",

author = "S. Trichon and M.H.A. Bonte and \{van den Boogaard\}, A.H. and J.-P. Ponthot",

year = "2007",

doi = "10.1063/1.2740857",

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isbn = "978-0-7354-0415-1",

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booktitle = "Materials processing and design: modeling, simulation and applications",

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note = "9th International Conference on Numerical Methods in Industrial Forming Processes, NUMIFORM 2007, NUMIFORM ; Conference date: 17-06-2007 Through 21-06-2007",

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Trichon, S, Bonte, MHA, van den Boogaard, AH & Ponthot, J-P 2007, A study for efficiently solving optimisation problems with an increasing number of design variables. in JMA César de Sá & AD Santos (eds), Materials processing and design: modeling, simulation and applications: NUMIFORM '07 : proceedings of the 9th International Conference on Numerical Methods in Industrial Forming Processes, Porto, Portugal, 17-21 June, 2007. American Institute of Physics, Melville, NY, pp. 481-486, 9th International Conference on Numerical Methods in Industrial Forming Processes, NUMIFORM 2007, Porto, Portugal, 17/06/07. https://doi.org/10.1063/1.2740857

A study for efficiently solving optimisation problems with an increasing number of design variables. / Trichon, S.; Bonte, M.H.A.; van den Boogaard, A.H. et al.
Materials processing and design: modeling, simulation and applications: NUMIFORM '07 : proceedings of the 9th International Conference on Numerical Methods in Industrial Forming Processes, Porto, Portugal, 17-21 June, 2007. ed. / J.M.A. César de Sá; Abel D. Santos. Melville, NY: American Institute of Physics, 2007. p. 481-486.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - A study for efficiently solving optimisation problems with an increasing number of design variables

AU - Trichon, S.

AU - Bonte, M.H.A.

AU - van den Boogaard, A.H.

AU - Ponthot, J.-P.

N1 - Conference code: 9

PY - 2007

Y1 - 2007

N2 - Coupling optimisation algorithms to Finite Element Methods (FEM) is a very promising way to achieve optimal metal forming processes. However, many optimisation algorithms exist and it is not clear which of these algorithms to use. This paper investigates the sensitivity of a Sequential Approximate Optimisation algorithm (SAO) proposed in [1–4] to an increasing number of design variables and compares it with two other algorithms: an Evolutionary Strategy (ES) and an Evolutionary version of the SAO (ESAO). In addition, it observes the influence of different Designs Of Experiments used with the SAO. It is concluded that the SAO is very capable and efficient and its combination with an ES is not beneficial. Moreover, the use of SAO with Fractional Factorial Design is the most efficient method, rather than Full Factorial Design as proposed in [1–4].

AB - Coupling optimisation algorithms to Finite Element Methods (FEM) is a very promising way to achieve optimal metal forming processes. However, many optimisation algorithms exist and it is not clear which of these algorithms to use. This paper investigates the sensitivity of a Sequential Approximate Optimisation algorithm (SAO) proposed in [1–4] to an increasing number of design variables and compares it with two other algorithms: an Evolutionary Strategy (ES) and an Evolutionary version of the SAO (ESAO). In addition, it observes the influence of different Designs Of Experiments used with the SAO. It is concluded that the SAO is very capable and efficient and its combination with an ES is not beneficial. Moreover, the use of SAO with Fractional Factorial Design is the most efficient method, rather than Full Factorial Design as proposed in [1–4].

KW - Metamodelling

KW - Design of Experiments (DoE)

KW - Numerical optimisation

U2 - 10.1063/1.2740857

DO - 10.1063/1.2740857

M3 - Conference contribution

SN - 978-0-7354-0415-1

SP - 481

EP - 486

BT - Materials processing and design: modeling, simulation and applications

A2 - César de Sá, J.M.A.

A2 - Santos, Abel D.

PB - American Institute of Physics

CY - Melville, NY

T2 - 9th International Conference on Numerical Methods in Industrial Forming Processes, NUMIFORM 2007

Y2 - 17 June 2007 through 21 June 2007

ER -

Trichon S, Bonte MHA, van den Boogaard AH, Ponthot JP. A study for efficiently solving optimisation problems with an increasing number of design variables. In César de Sá JMA, Santos AD, editors, Materials processing and design: modeling, simulation and applications: NUMIFORM '07 : proceedings of the 9th International Conference on Numerical Methods in Industrial Forming Processes, Porto, Portugal, 17-21 June, 2007. Melville, NY: American Institute of Physics. 2007. p. 481-486 doi: 10.1063/1.2740857

A study for efficiently solving optimisation problems with an increasing number of design variables

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Conference

Keywords

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