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A new optimization scheme for robust design modeling with unbalanced data

The Lin and Tu (LT) optimization scheme which is based on mean squared error (MSE) objective function is the commonly used optimization scheme for estimating the optimal mean response in robust dual response surface optimization. The ordinary least squares (OLS) method is often used to estimate the...

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Main Authors: Baba, Ishaq, Midi, Habshah, Ibragimov, Gafurjan, Rana, Md. Sohel
Format: Article
Published: Penerbit Universiti Kebangsaan Malaysia 2021
Online Access:http://psasir.upm.edu.my/id/eprint/95843/
https://www.ukm.my/jsm/malay_journals/jilid51bil5_2022/KandunganJilid51Bil5_2022.html
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spelling my.upm.eprints.958432023-03-29T03:28:25Z http://psasir.upm.edu.my/id/eprint/95843/ A new optimization scheme for robust design modeling with unbalanced data Baba, Ishaq Midi, Habshah Ibragimov, Gafurjan Rana, Md. Sohel The Lin and Tu (LT) optimization scheme which is based on mean squared error (MSE) objective function is the commonly used optimization scheme for estimating the optimal mean response in robust dual response surface optimization. The ordinary least squares (OLS) method is often used to estimate the parameters of the process location and process scale models of the responses. However, the OLS is not efficient for the unbalanced design data since this kind of data make the errors of a model become heteroscedastic, which produces large standard errors of the estimates. To remedy this problem, a weighted least squares (WLS) method is put forward. Since the LT optimization scheme produces a large difference between the estimates of the mean response and the experimenter actual target value, we propose a new optimization scheme. The OLS and the WLS are integrated in the proposed scheme to determine the optimal solution of the estimated responses. The results of the simulation study and real example indicate that the WLS is superior when compared with the OLS method irrespective of the optimization scheme used. However, the combination of WLS and the proposed optimization scheme (PFO) signify more efficient results when compared to the WLS combined with the LT optimization scheme. Penerbit Universiti Kebangsaan Malaysia 2021 Article PeerReviewed Baba, Ishaq and Midi, Habshah and Ibragimov, Gafurjan and Rana, Md. Sohel (2021) A new optimization scheme for robust design modeling with unbalanced data. Sains Malaysiana, 51 (5). pp. 1577-1586. ISSN 0126-6039 https://www.ukm.my/jsm/malay_journals/jilid51bil5_2022/KandunganJilid51Bil5_2022.html 10.17576/jsm-2022-5105-25
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
description The Lin and Tu (LT) optimization scheme which is based on mean squared error (MSE) objective function is the commonly used optimization scheme for estimating the optimal mean response in robust dual response surface optimization. The ordinary least squares (OLS) method is often used to estimate the parameters of the process location and process scale models of the responses. However, the OLS is not efficient for the unbalanced design data since this kind of data make the errors of a model become heteroscedastic, which produces large standard errors of the estimates. To remedy this problem, a weighted least squares (WLS) method is put forward. Since the LT optimization scheme produces a large difference between the estimates of the mean response and the experimenter actual target value, we propose a new optimization scheme. The OLS and the WLS are integrated in the proposed scheme to determine the optimal solution of the estimated responses. The results of the simulation study and real example indicate that the WLS is superior when compared with the OLS method irrespective of the optimization scheme used. However, the combination of WLS and the proposed optimization scheme (PFO) signify more efficient results when compared to the WLS combined with the LT optimization scheme.
format Article
author Baba, Ishaq
Midi, Habshah
Ibragimov, Gafurjan
Rana, Md. Sohel
spellingShingle Baba, Ishaq
Midi, Habshah
Ibragimov, Gafurjan
Rana, Md. Sohel
A new optimization scheme for robust design modeling with unbalanced data
author_facet Baba, Ishaq
Midi, Habshah
Ibragimov, Gafurjan
Rana, Md. Sohel
author_sort Baba, Ishaq
title A new optimization scheme for robust design modeling with unbalanced data
title_short A new optimization scheme for robust design modeling with unbalanced data
title_full A new optimization scheme for robust design modeling with unbalanced data
title_fullStr A new optimization scheme for robust design modeling with unbalanced data
title_full_unstemmed A new optimization scheme for robust design modeling with unbalanced data
title_sort new optimization scheme for robust design modeling with unbalanced data
publisher Penerbit Universiti Kebangsaan Malaysia
publishDate 2021
url http://psasir.upm.edu.my/id/eprint/95843/
https://www.ukm.my/jsm/malay_journals/jilid51bil5_2022/KandunganJilid51Bil5_2022.html
_version_ 1761673197753729024
score 13.211869

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