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Surrogate-Based Reduced-Dimension Global Optimization in Process Systems Engineering

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High-Dimensional Optimization and Probability

Part of the book series: Springer Optimization and Its Applications ((SOIA,volume 191))

Abstract

High dimensional global optimization problems arise frequently in process systems engineering. This is a result of the complex mechanistic relationships that describe process systems, and/or their large-scale nature. High dimensional optimization problems can often be more easily solved by instead solving a sequence of reduced-dimension subproblems. Surrogate models can allow the formulation of reduced-dimension subproblems by approximating the key features of the original model. Surrogate-based optimization (SBO) is to use surrogate modeling to solve a sequence of approximate reduced-dimension subproblems, in order to converge to a high quality solution to the original high dimensional problem. Here we review the key characteristics of SBO frameworks and their application to process systems optimization problems.

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Acknowledgements

This research was supported by Natural Sciences and Engineering Research Council of Canada (NSERC) through the Discovery Grant (RGPIN-2019-05217).

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Authors and Affiliations

  1. Department of Chemical Engineering, Queen’s University, Kingston, ON, Canada

    Kody Kazda & **ang Li

Authors
  1. Kody Kazda
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  2. **ang Li
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Correspondence to **ang Li .

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Editors and Affiliations

  1. Institut für Mathematik, Universität Zürich, Zürich, Switzerland

    Ashkan Nikeghbali

  2. Dept. of Industrial & Systems Eng., University of Florida, Gainesville, FL, USA

    Panos M. Pardalos

  3. Moscow Institute of Physics & Technology, Dolgoprudny, Russia

    Andrei M. Raigorodskii

  4. Department of Mathematics and Engineering Sciences, Hellenic Military Academy, Athens, Greece

    Michael Th. Rassias

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Kazda, K., Li, X. (2022). Surrogate-Based Reduced-Dimension Global Optimization in Process Systems Engineering. In: Nikeghbali, A., Pardalos, P.M., Raigorodskii, A.M., Rassias, M.T. (eds) High-Dimensional Optimization and Probability. Springer Optimization and Its Applications, vol 191. Springer, Cham. https://doi.org/10.1007/978-3-031-00832-0_10

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