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Hybrid Algorithm for Risk Conscious Chemical Batch Planning Under Uncertainty

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Modeling, Simulation and Optimization of Complex Processes

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Abstract

We consider planning problems of flexible chemical batch processes paying special attention to uncertainties in problem data. The optimization problems are formulated as two-stage stochastic mixed-integer models in which some of the decisions (first-stage) have to be made under uncertainty and the remaining decisions (second-stage) can be made after the realization of the uncertain parameters. The uncertain model parameters are represented by a finite set of scenarios. The risk conscious planning problem under uncertainty is solved by a stage decomposition approach using a multi-objective evolutionary algorithm which optimizes the expected scenario costs and the risk criterion with respect to the first-stage decisions. The second-stage scenario decisions are handled by mathematical programming. Results from numerical experiments for a multi-product batch plant are presented.

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Authors and Affiliations

  1. Process Dynamics and Operations Group, Department of Biochemical and Chemical Engineering, Technische Universität Dortmund, 44221, Dortmund, Germany

    Thomas Tometzki & Sebastian Engell

Authors
  1. Thomas Tometzki
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  2. Sebastian Engell
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Correspondence to Thomas Tometzki .

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Editors and Affiliations

  1. Interdisziplinäres Zentrum für, Wissenschaftliches Rechnen (IWR), Universität Heidelberg, Im Neuenheimer Feld 368, Heidelberg, 69120, Germany

    Hans Georg Bock

  2. and Technology (VAST), Institute of Mathematics, Vietnamese Academy of Science, Hoang Quoc Viet Road, Hanoi, 10307, Vietnam

    Xuan Phu Hoang

  3. , Interdisciplinary Center for, University of Heidelberg, Im Neuenheimer Feld 368, Heidelberg, 69120, Germany

    Rolf Rannacher

  4. , Interdisciplinary Center for, University of Heidelberg, Im Neuenheimer Feld 368, Heidelberg, 69120, Germany

    Johannes P. Schlöder

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© 2012 Springer-Verlag Berlin Heidelberg

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Tometzki, T., Engell, S. (2012). Hybrid Algorithm for Risk Conscious Chemical Batch Planning Under Uncertainty. In: Bock, H., Hoang, X., Rannacher, R., Schlöder, J. (eds) Modeling, Simulation and Optimization of Complex Processes. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25707-0_24

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