An overview on robust design hybrid metamodeling: Advanced methodology in process optimization under uncertainty
Nowadays, process optimization has been an interest in engineering design for improving the performance and reducing cost. In practice, in addition to uncertainty or noise parameters, a comprehensive optimization model must be able to attend other circumstances which might be imposed in problems und...
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Growing Science
2017
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Online Access: | http://psasir.upm.edu.my/id/eprint/60839/1/An%20overview%20on%20robust%20design%20hybrid%20metamodeling%20Advanced%20methodology%20in%20process%20optimization%20under%20uncertainty.pdf http://psasir.upm.edu.my/id/eprint/60839/ http://growingscience.com/beta/ijiec/2555-an-overview-on-robust-design-hybrid-metamodeling-advanced-methodology-in-process-optimization-under-uncertainty.html |
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my.upm.eprints.608392019-04-26T08:48:50Z http://psasir.upm.edu.my/id/eprint/60839/ An overview on robust design hybrid metamodeling: Advanced methodology in process optimization under uncertainty Parnianifard, Amir Ahmad, Siti Azfanizam Mohd Ariffin, Mohd Khairol Anuar Ismail, Mohd Idris Shah Nowadays, process optimization has been an interest in engineering design for improving the performance and reducing cost. In practice, in addition to uncertainty or noise parameters, a comprehensive optimization model must be able to attend other circumstances which might be imposed in problems under real operational conditions such as dynamic objectives, multi-response, various probabilistic distribution, discrete and continuous data, physical constraints to design parameters, performance cost, computational complexity and multi-process environment. The main goal of this paper is to give a general overview of topics with brief systematic review and concise discussions about the recent development of comprehensive robust design optimization methods under hybrid aforesaid circumstances. Both optimization methods of mathematical programming based on Taguchi approach and robust optimization based on scenario sets are briefly described. Metamodels hybrid robust design is discussed as an appropriate methodology to decrease computational complexity in problems under uncertainty. In this context, the authors’ policy is to choose important topics for giving a systematic picture to those who wish to be more familiar with recent studies about robust design optimization hybrid metamodels, also by attending real circumstances in practice. In particular, production and project management are considered as two important methodologies that could be improved by applications of advanced robust design combining with metamodel methods. Growing Science 2017 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/60839/1/An%20overview%20on%20robust%20design%20hybrid%20metamodeling%20Advanced%20methodology%20in%20process%20optimization%20under%20uncertainty.pdf Parnianifard, Amir and Ahmad, Siti Azfanizam and Mohd Ariffin, Mohd Khairol Anuar and Ismail, Mohd Idris Shah (2017) An overview on robust design hybrid metamodeling: Advanced methodology in process optimization under uncertainty. International Journal of Industrial Engineering Computations, 9 (1). pp. 1-32. ISSN 1923-2926; ESSN: 1923-2934 http://growingscience.com/beta/ijiec/2555-an-overview-on-robust-design-hybrid-metamodeling-advanced-methodology-in-process-optimization-under-uncertainty.html 10.5267/j.ijiec.2017.5.003 |
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Nowadays, process optimization has been an interest in engineering design for improving the performance and reducing cost. In practice, in addition to uncertainty or noise parameters, a comprehensive optimization model must be able to attend other circumstances which might be imposed in problems under real operational conditions such as dynamic objectives, multi-response, various probabilistic distribution, discrete and continuous data, physical constraints to design parameters, performance cost, computational complexity and multi-process environment. The main goal of this paper is to give a general overview of topics with brief systematic review and concise discussions about the recent development of comprehensive robust design optimization methods under hybrid aforesaid circumstances. Both optimization methods of mathematical programming based on Taguchi approach and robust optimization based on scenario sets are briefly described. Metamodels hybrid robust design is discussed as an appropriate methodology to decrease computational complexity in problems under uncertainty. In this context, the authors’ policy is to choose important topics for giving a systematic picture to those who wish to be more familiar with recent studies about robust design optimization hybrid metamodels, also by attending real circumstances in practice. In particular, production and project management are considered as two important methodologies that could be improved by applications of advanced robust design combining with metamodel methods. |
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Article |
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Parnianifard, Amir Ahmad, Siti Azfanizam Mohd Ariffin, Mohd Khairol Anuar Ismail, Mohd Idris Shah |
spellingShingle |
Parnianifard, Amir Ahmad, Siti Azfanizam Mohd Ariffin, Mohd Khairol Anuar Ismail, Mohd Idris Shah An overview on robust design hybrid metamodeling: Advanced methodology in process optimization under uncertainty |
author_facet |
Parnianifard, Amir Ahmad, Siti Azfanizam Mohd Ariffin, Mohd Khairol Anuar Ismail, Mohd Idris Shah |
author_sort |
Parnianifard, Amir |
title |
An overview on robust design hybrid metamodeling: Advanced methodology in process optimization under uncertainty |
title_short |
An overview on robust design hybrid metamodeling: Advanced methodology in process optimization under uncertainty |
title_full |
An overview on robust design hybrid metamodeling: Advanced methodology in process optimization under uncertainty |
title_fullStr |
An overview on robust design hybrid metamodeling: Advanced methodology in process optimization under uncertainty |
title_full_unstemmed |
An overview on robust design hybrid metamodeling: Advanced methodology in process optimization under uncertainty |
title_sort |
overview on robust design hybrid metamodeling: advanced methodology in process optimization under uncertainty |
publisher |
Growing Science |
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2017 |
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http://psasir.upm.edu.my/id/eprint/60839/1/An%20overview%20on%20robust%20design%20hybrid%20metamodeling%20Advanced%20methodology%20in%20process%20optimization%20under%20uncertainty.pdf http://psasir.upm.edu.my/id/eprint/60839/ http://growingscience.com/beta/ijiec/2555-an-overview-on-robust-design-hybrid-metamodeling-advanced-methodology-in-process-optimization-under-uncertainty.html |
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