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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, Habshah Midi,, Ibragimov, Gafurjan, Rana, Sohel
Format: Article
Language:English
Published: Penerbit Universiti Kebangsaan Malaysia 2022
Online Access:http://journalarticle.ukm.my/19489/1/25.pdf
http://journalarticle.ukm.my/19489/
https://www.ukm.my/jsm/malay_journals/jilid51bil5_2022/KandunganJilid51Bil5_2022.html
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spelling my-ukm.journal.194892022-08-26T02:36:14Z http://journalarticle.ukm.my/19489/ A new optimization scheme for robust design modeling with unbalanced data Baba, Ishaq Habshah Midi, Ibragimov, Gafurjan Rana, 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 2022-05 Article PeerReviewed application/pdf en http://journalarticle.ukm.my/19489/1/25.pdf Baba, Ishaq and Habshah Midi, and Ibragimov, Gafurjan and Rana, Sohel (2022) 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
institution Universiti Kebangsaan Malaysia
building Tun Sri Lanang Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Kebangsaan Malaysia
content_source UKM Journal Article Repository
url_provider http://journalarticle.ukm.my/
language English
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
Habshah Midi,
Ibragimov, Gafurjan
Rana, Sohel
spellingShingle Baba, Ishaq
Habshah Midi,
Ibragimov, Gafurjan
Rana, Sohel
A new optimization scheme for robust design modeling with unbalanced data
author_facet Baba, Ishaq
Habshah Midi,
Ibragimov, Gafurjan
Rana, 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 2022
url http://journalarticle.ukm.my/19489/1/25.pdf
http://journalarticle.ukm.my/19489/
https://www.ukm.my/jsm/malay_journals/jilid51bil5_2022/KandunganJilid51Bil5_2022.html
_version_ 1743108007355482112
score 13.211869

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