The mixture design threshold accepting algorithm for generating $$\varvec{D}$$-optimal designs of the mixture models
Abstract This paper proposes a target specialized meta-heuristic optimization algorithm, called Mixture Design Threshold Accepting (MDTA) algorithm, which applies the idea of the Threshold Accepting to generate the corresponding approximate D-optimal designs for a wide range of mixture models, with...
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| Autor*in: |
Wang, Haoyu [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2021 |
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| Schlagwörter: |
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| Anmerkung: |
© The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021 |
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| Übergeordnetes Werk: |
Enthalten in: Metrika - Springer Berlin Heidelberg, 1958, 85(2021), 3 vom: 15. Juli, Seite 345-371 |
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| Übergeordnetes Werk: |
volume:85 ; year:2021 ; number:3 ; day:15 ; month:07 ; pages:345-371 |
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| DOI / URN: |
10.1007/s00184-021-00832-3 |
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OLC2078164615 |
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| 520 | |a Abstract This paper proposes a target specialized meta-heuristic optimization algorithm, called Mixture Design Threshold Accepting (MDTA) algorithm, which applies the idea of the Threshold Accepting to generate the corresponding approximate D-optimal designs for a wide range of mixture models, with or without constraints imposed on the components. The MDTA algorithm is tested by many of common mixture models, among which some even have no solutions of the D-optimal design available in the literature. Other tests include 5 models with specific upper bound constraints. These results prove that the MDTA algorithm is very efficient in finding D-optimal designs for mixture models. In some scenarios it even outperforms the state-of-art algorithms, such as the ProjPSO algorithm and the REX algorithm. The source codes of the MDTA algorithm are freely available by writing to the first author. | ||
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10.1007/s00184-021-00832-3 doi (DE-627)OLC2078164615 (DE-He213)s00184-021-00832-3-p DE-627 ger DE-627 rakwb eng 510 VZ Wang, Haoyu verfasserin (orcid)0000-0002-5450-4066 aut The mixture design threshold accepting algorithm for generating $$\varvec{D}$$-optimal designs of the mixture models 2021 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021 Abstract This paper proposes a target specialized meta-heuristic optimization algorithm, called Mixture Design Threshold Accepting (MDTA) algorithm, which applies the idea of the Threshold Accepting to generate the corresponding approximate D-optimal designs for a wide range of mixture models, with or without constraints imposed on the components. The MDTA algorithm is tested by many of common mixture models, among which some even have no solutions of the D-optimal design available in the literature. Other tests include 5 models with specific upper bound constraints. These results prove that the MDTA algorithm is very efficient in finding D-optimal designs for mixture models. In some scenarios it even outperforms the state-of-art algorithms, such as the ProjPSO algorithm and the REX algorithm. The source codes of the MDTA algorithm are freely available by writing to the first author. Mixture experiment Optimal design Mixture model Meta-heuristic algorithm Zhang, Chongqi aut Enthalten in Metrika Springer Berlin Heidelberg, 1958 85(2021), 3 vom: 15. Juli, Seite 345-371 (DE-627)12908171X (DE-600)3502-6 (DE-576)014414619 0026-1335 nnns volume:85 year:2021 number:3 day:15 month:07 pages:345-371 https://doi.org/10.1007/s00184-021-00832-3 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OLC-WIW SSG-OPC-MAT GBV_ILN_267 GBV_ILN_2018 GBV_ILN_4027 GBV_ILN_4277 AR 85 2021 3 15 07 345-371 |
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10.1007/s00184-021-00832-3 doi (DE-627)OLC2078164615 (DE-He213)s00184-021-00832-3-p DE-627 ger DE-627 rakwb eng 510 VZ Wang, Haoyu verfasserin (orcid)0000-0002-5450-4066 aut The mixture design threshold accepting algorithm for generating $$\varvec{D}$$-optimal designs of the mixture models 2021 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021 Abstract This paper proposes a target specialized meta-heuristic optimization algorithm, called Mixture Design Threshold Accepting (MDTA) algorithm, which applies the idea of the Threshold Accepting to generate the corresponding approximate D-optimal designs for a wide range of mixture models, with or without constraints imposed on the components. The MDTA algorithm is tested by many of common mixture models, among which some even have no solutions of the D-optimal design available in the literature. Other tests include 5 models with specific upper bound constraints. These results prove that the MDTA algorithm is very efficient in finding D-optimal designs for mixture models. In some scenarios it even outperforms the state-of-art algorithms, such as the ProjPSO algorithm and the REX algorithm. The source codes of the MDTA algorithm are freely available by writing to the first author. Mixture experiment Optimal design Mixture model Meta-heuristic algorithm Zhang, Chongqi aut Enthalten in Metrika Springer Berlin Heidelberg, 1958 85(2021), 3 vom: 15. Juli, Seite 345-371 (DE-627)12908171X (DE-600)3502-6 (DE-576)014414619 0026-1335 nnns volume:85 year:2021 number:3 day:15 month:07 pages:345-371 https://doi.org/10.1007/s00184-021-00832-3 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OLC-WIW SSG-OPC-MAT GBV_ILN_267 GBV_ILN_2018 GBV_ILN_4027 GBV_ILN_4277 AR 85 2021 3 15 07 345-371 |
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10.1007/s00184-021-00832-3 doi (DE-627)OLC2078164615 (DE-He213)s00184-021-00832-3-p DE-627 ger DE-627 rakwb eng 510 VZ Wang, Haoyu verfasserin (orcid)0000-0002-5450-4066 aut The mixture design threshold accepting algorithm for generating $$\varvec{D}$$-optimal designs of the mixture models 2021 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021 Abstract This paper proposes a target specialized meta-heuristic optimization algorithm, called Mixture Design Threshold Accepting (MDTA) algorithm, which applies the idea of the Threshold Accepting to generate the corresponding approximate D-optimal designs for a wide range of mixture models, with or without constraints imposed on the components. The MDTA algorithm is tested by many of common mixture models, among which some even have no solutions of the D-optimal design available in the literature. Other tests include 5 models with specific upper bound constraints. These results prove that the MDTA algorithm is very efficient in finding D-optimal designs for mixture models. In some scenarios it even outperforms the state-of-art algorithms, such as the ProjPSO algorithm and the REX algorithm. The source codes of the MDTA algorithm are freely available by writing to the first author. Mixture experiment Optimal design Mixture model Meta-heuristic algorithm Zhang, Chongqi aut Enthalten in Metrika Springer Berlin Heidelberg, 1958 85(2021), 3 vom: 15. Juli, Seite 345-371 (DE-627)12908171X (DE-600)3502-6 (DE-576)014414619 0026-1335 nnns volume:85 year:2021 number:3 day:15 month:07 pages:345-371 https://doi.org/10.1007/s00184-021-00832-3 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OLC-WIW SSG-OPC-MAT GBV_ILN_267 GBV_ILN_2018 GBV_ILN_4027 GBV_ILN_4277 AR 85 2021 3 15 07 345-371 |
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10.1007/s00184-021-00832-3 doi (DE-627)OLC2078164615 (DE-He213)s00184-021-00832-3-p DE-627 ger DE-627 rakwb eng 510 VZ Wang, Haoyu verfasserin (orcid)0000-0002-5450-4066 aut The mixture design threshold accepting algorithm for generating $$\varvec{D}$$-optimal designs of the mixture models 2021 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021 Abstract This paper proposes a target specialized meta-heuristic optimization algorithm, called Mixture Design Threshold Accepting (MDTA) algorithm, which applies the idea of the Threshold Accepting to generate the corresponding approximate D-optimal designs for a wide range of mixture models, with or without constraints imposed on the components. The MDTA algorithm is tested by many of common mixture models, among which some even have no solutions of the D-optimal design available in the literature. Other tests include 5 models with specific upper bound constraints. These results prove that the MDTA algorithm is very efficient in finding D-optimal designs for mixture models. In some scenarios it even outperforms the state-of-art algorithms, such as the ProjPSO algorithm and the REX algorithm. The source codes of the MDTA algorithm are freely available by writing to the first author. Mixture experiment Optimal design Mixture model Meta-heuristic algorithm Zhang, Chongqi aut Enthalten in Metrika Springer Berlin Heidelberg, 1958 85(2021), 3 vom: 15. Juli, Seite 345-371 (DE-627)12908171X (DE-600)3502-6 (DE-576)014414619 0026-1335 nnns volume:85 year:2021 number:3 day:15 month:07 pages:345-371 https://doi.org/10.1007/s00184-021-00832-3 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OLC-WIW SSG-OPC-MAT GBV_ILN_267 GBV_ILN_2018 GBV_ILN_4027 GBV_ILN_4277 AR 85 2021 3 15 07 345-371 |
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10.1007/s00184-021-00832-3 doi (DE-627)OLC2078164615 (DE-He213)s00184-021-00832-3-p DE-627 ger DE-627 rakwb eng 510 VZ Wang, Haoyu verfasserin (orcid)0000-0002-5450-4066 aut The mixture design threshold accepting algorithm for generating $$\varvec{D}$$-optimal designs of the mixture models 2021 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021 Abstract This paper proposes a target specialized meta-heuristic optimization algorithm, called Mixture Design Threshold Accepting (MDTA) algorithm, which applies the idea of the Threshold Accepting to generate the corresponding approximate D-optimal designs for a wide range of mixture models, with or without constraints imposed on the components. The MDTA algorithm is tested by many of common mixture models, among which some even have no solutions of the D-optimal design available in the literature. Other tests include 5 models with specific upper bound constraints. These results prove that the MDTA algorithm is very efficient in finding D-optimal designs for mixture models. In some scenarios it even outperforms the state-of-art algorithms, such as the ProjPSO algorithm and the REX algorithm. The source codes of the MDTA algorithm are freely available by writing to the first author. Mixture experiment Optimal design Mixture model Meta-heuristic algorithm Zhang, Chongqi aut Enthalten in Metrika Springer Berlin Heidelberg, 1958 85(2021), 3 vom: 15. Juli, Seite 345-371 (DE-627)12908171X (DE-600)3502-6 (DE-576)014414619 0026-1335 nnns volume:85 year:2021 number:3 day:15 month:07 pages:345-371 https://doi.org/10.1007/s00184-021-00832-3 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OLC-WIW SSG-OPC-MAT GBV_ILN_267 GBV_ILN_2018 GBV_ILN_4027 GBV_ILN_4277 AR 85 2021 3 15 07 345-371 |
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The mixture design threshold accepting algorithm for generating $$\varvec{D}$$-optimal designs of the mixture models |
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Abstract This paper proposes a target specialized meta-heuristic optimization algorithm, called Mixture Design Threshold Accepting (MDTA) algorithm, which applies the idea of the Threshold Accepting to generate the corresponding approximate D-optimal designs for a wide range of mixture models, with or without constraints imposed on the components. The MDTA algorithm is tested by many of common mixture models, among which some even have no solutions of the D-optimal design available in the literature. Other tests include 5 models with specific upper bound constraints. These results prove that the MDTA algorithm is very efficient in finding D-optimal designs for mixture models. In some scenarios it even outperforms the state-of-art algorithms, such as the ProjPSO algorithm and the REX algorithm. The source codes of the MDTA algorithm are freely available by writing to the first author. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021 |
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Abstract This paper proposes a target specialized meta-heuristic optimization algorithm, called Mixture Design Threshold Accepting (MDTA) algorithm, which applies the idea of the Threshold Accepting to generate the corresponding approximate D-optimal designs for a wide range of mixture models, with or without constraints imposed on the components. The MDTA algorithm is tested by many of common mixture models, among which some even have no solutions of the D-optimal design available in the literature. Other tests include 5 models with specific upper bound constraints. These results prove that the MDTA algorithm is very efficient in finding D-optimal designs for mixture models. In some scenarios it even outperforms the state-of-art algorithms, such as the ProjPSO algorithm and the REX algorithm. The source codes of the MDTA algorithm are freely available by writing to the first author. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021 |
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Abstract This paper proposes a target specialized meta-heuristic optimization algorithm, called Mixture Design Threshold Accepting (MDTA) algorithm, which applies the idea of the Threshold Accepting to generate the corresponding approximate D-optimal designs for a wide range of mixture models, with or without constraints imposed on the components. The MDTA algorithm is tested by many of common mixture models, among which some even have no solutions of the D-optimal design available in the literature. Other tests include 5 models with specific upper bound constraints. These results prove that the MDTA algorithm is very efficient in finding D-optimal designs for mixture models. In some scenarios it even outperforms the state-of-art algorithms, such as the ProjPSO algorithm and the REX algorithm. The source codes of the MDTA algorithm are freely available by writing to the first author. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021 |
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| title_short |
The mixture design threshold accepting algorithm for generating $$\varvec{D}$$-optimal designs of the mixture models |
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https://doi.org/10.1007/s00184-021-00832-3 |
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Zhang, Chongqi |
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2024-07-03T19:07:14.572Z |
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