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Recent developments in metamodel based robust black-box simulation optimization: An overview

In this state-of the art review paper, a systematic qualitative and quantitative review is implemented among Metamodel Based Robust Simulation Optimization (MBRSO) for black-box and expensive simulation models under uncertainty. | Recent developments in metamodel based robust black-box simulation optimization An overview Decision Science Letters 8 2019 17 44 Contents lists available at GrowingScience Decision Science Letters homepage www.GrowingScience.com dsl Recent developments in metamodel based robust black-box simulation optimization An overview Amir Parnianifarda A.S. Azfanizama M.K.A. Ariffina M.I.S. Ismaila and Nader Ale Ebrahimb aDepartment of Mechanical and Manufacturing Engineering Faculty of Engineering Universiti Putra Malaysia 43400 UPM Serdang Selangor Malaysia bCenter for Research Services Institute of Research Management and Monitoring IPPP University of Malaya Kuala Lumpur Malaysia CHRONICLE ABSTRACT Article history In the real world of engineering problems in order to reduce optimization costs in physical Received January 18 2018 processes running simulation experiments in the format of computer codes have been conducted. Received in revised format It is desired to improve the validity of simulation-optimization results by attending the source of May 10 2018 variability in the model s output s . Uncertainty can increase complexity and computational costs Accepted May 11 2018 Available online in Designing and Analyzing of Computer Experiments DACE . In this state-of the art review May 23 2018 paper a systematic qualitative and quantitative review is implemented among Metamodel Based Keywords Robust Simulation Optimization MBRSO for black-box and expensive simulation models Simulation optimization under uncertainty. This context is focused on the management of uncertainty particularly based Robust design on the Taguchi worldview on robust design and robust optimization methods in the class of dual Metamodel response methodology when simulation optimization can be handled by surrogates. At the end Polynomial regression while both trends and gaps in the research field are highlighted some suggestions for future Kriging research are directed. Computer experiments 2018 by the