Stochastic Optimization for Operating Chemical Processes Under Uncertainty

Please always quote using this URN: urn:nbn:de:0297-zib-6304
  • Mathematical optimization techniques are on their way to becoming a standard tool in chemical process engineering. While such approaches are usually based on deterministic models, uncertainties such as external disturbances play a significant role in many real-life applications. The present article gives an introduction to practical issues of process operation and to basic mathematical concepts required for the explicit treatment of uncertainties by stochastic optimization.

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Metadaten
Author:Rene Henrion, Pu Li, Andris Möller, Marc C. Steinbach, Moritz Wendt, Günter Wozny
Document Type:ZIB-Report
Tag:Chemical Processes; Multistage Stochastic Programs; Probabilistic Constraints; Uncertainty
MSC-Classification:90-XX OPERATIONS RESEARCH, MATHEMATICAL PROGRAMMING / 90Cxx Mathematical programming [See also 49Mxx, 65Kxx] / 90C06 Large-scale problems
90-XX OPERATIONS RESEARCH, MATHEMATICAL PROGRAMMING / 90Cxx Mathematical programming [See also 49Mxx, 65Kxx] / 90C15 Stochastic programming
90-XX OPERATIONS RESEARCH, MATHEMATICAL PROGRAMMING / 90Cxx Mathematical programming [See also 49Mxx, 65Kxx] / 90C30 Nonlinear programming
92-XX BIOLOGY AND OTHER NATURAL SCIENCES / 92Exx Chemistry (For biochemistry, see 92C40) / 92E20 Classical flows, reactions, etc. [See also 80A30, 80A32]
Date of first Publication:2001/03/26
Series (Serial Number):ZIB-Report (01-04)
Published in:Appeared in: Online Optimization of Large Scale Systems, M. Grötschel, S. O. Krumke, J. Rambau (eds.) Springer, 2001, pp. 457-478