Chemical Engineering

Robust Optimization in Nanoparticle Technology: A Proof of Principle by Quantum Dot Growth in a Residence Time Reactor

  • Kevin-Martin Aigner
  • Frauke Liers
  • Jana Dienstbier
  • Wolfgang Peukert
  • Lukas Pflug
  • Jan Hendrik Rolfes
  • Doris Segets
    • Categories Chemical Engineering, Robust Optimization Tags , , ,

    Knowledge-based determination of the best-possible experimental setups for nanoparticle design is highly challenging. Additionally, such processes are accompanied by noticeable uncertainties. Therefore, protection against these uncertainties is needed. Robust optimization helps determining such best possible processes. The latter guarantees quality requirements regardless of how the uncertainties, e.g. with regard to variations in raw materials, heat … Read more

    Two decades of blackbox optimization applications

  • Stéphane Alarie
  • Charles Audet
  • Aïmen E. Gheribi
  • Michael Kokkolaras
  • Sébastien Le Digabel
    • Categories Applications - Science and Engineering, Chemical Engineering, Mechanical Engineering Tags , , ,

    This work reviews blackbox optimization applications over the last twenty years, addressed using direct search optimization methods. Emphasis is placed on the Mesh Adaptive Direct Search (MADS) derivative-free optimization algorithm. The core of the document describes applications in three specific fields: Energy, materials science, and computational engineering design. Other applications in science and engineering as … Read more

    The Bipartite Boolean Quadric Polytope with Multiple-Choice Constraints

  • Andreas Bärmann
  • Alexander Martin
  • Oskar Schneider
    • Categories (Mixed) Integer Nonlinear Programming, Chemical Engineering, Polyhedra Tags , , , ,

    We consider the bipartite boolean quadric polytope (BQP) with multiple-choice constraints and analyse its combinatorial properties. The well-studied BQP is defined as the convex hull of all quadric incidence vectors over a bipartite graph. In this work, we study the case where there is a partition on one of the two bipartite node sets such … Read more

    Optimal design of an electricity-intensive industrial facility subject to electricity price uncertainty: stochastic optimization and scenario reduction

  • Adam R. Brandt
  • Holger Teichgraeber
    • Categories Chemical Engineering, Production and Logistics, Stochastic Programming Tags , , , ,

    When considering the design of electricity-intensive industrial processes, a challenge is that future electricity prices are highly uncertain. Design decisions made before construction can affect operations decades into the future. We thus explore whether including electricity price uncertainty into the design process affects design decisions. We apply stochastic optimization to the design and operations of … Read more

    Mixed-Integer Optimal Control for Multimodal Chromatography

  • Hans Georg Bock
  • Christian Kirches
  • Andreas Potschka
  • Dominik H. Cebulla
    • Categories (Mixed) Integer Nonlinear Programming, Chemical Engineering, Systems governed by Differential Equations Optimization Tags , , ,

    Multimodal chromatography is a powerful tool in the downstream processing of biopharmaceuticals. To fully benefit from this technology, an efficient process strategy must be determined beforehand. To facilitate this task, we employ a recent mechanistic model for multimodal chromatography, which takes salt concentration and pH into account, and we present a mathematical framework for the … Read more

    Clustering methods to find representative periods for the optimization of energy systems: an initial framework and comparison

  • Adam R. Brandt
  • Holger Teichgraeber
    • Categories Applications - Science and Engineering, Chemical Engineering, Energy Tags , , , , ,

    Modeling time-varying operations in complex energy systems optimization problems is often computationally intractable, and time-series input data are thus often aggregated to representative periods. In this work, we introduce a framework for using clustering methods for this purpose, and we compare both conventionally-used methods (k-means, k-medoids, and hierarchical clustering), and shape-based clustering methods (dynamic time … Read more

    The Synthesis Problem of Decentralized Energy Systems is strongly NP-hard

  • Martin Comis
  • Sebastian Goderbauer
  • Felix J. L. Willamowski
    • Categories Applications - Science and Engineering, Chemical Engineering, Combinatorial Optimization

    We analyze the computational complexity of the synthesis problem of decentralized energy systems. This synthesis problem consists of combining various types of energy conversion units and determining their sizing as well as operations in order to meet time-varying energy demands while maximizing an objective function, e.g., the net present value. In this paper, we prove … Read more

    Strong Convex Nonlinear Relaxations of the Pooling Problem

  • Claudia D'Ambrosio
  • Jeff Linderoth
  • James R. Luedtke
  • Jonas Schweiger
    • Categories Chemical Engineering, Cutting Plane Approaches, Global Optimization Tags , ,

    We investigate new convex relaxations for the pooling problem, a classic nonconvex production planning problem in which input materials are mixed in intermediate pools, with the outputs of these pools further mixed to make output products meeting given attribute percentage requirements. Our relaxations are derived by considering a set which arises from the formulation by … Read more

    Deterministic Global Optimization with Artificial Neural Networks Embedded

  • Alexander Mitsos
  • Artur M Schweidtmann
    • Categories Chemical Engineering, Global Optimization, Nonlinear Optimization Tags , , , , , , ,

    Artificial neural networks (ANNs) are used in various applications for data-driven black-box modeling and subsequent optimization. Herein, we present an efficient method for deterministic global optimization of ANN embedded optimization problems. The proposed method is based on relaxations of algorithms using McCormick relaxations in a reduced-space [\textit{SIOPT}, 20 (2009), pp. 573-601] including the convex and … Read more

    Data-Driven Robust Optimization Based on Kernel Learning

  • Xiaolin Huang
  • Chao Shang
  • Fengqi You
    • Categories Chemical Engineering, Robust Optimization Tags , , , ,

    We propose piecewise linear kernel-based support vector clustering (SVC) as a new approach tailored to data-driven robust optimization. By solving a quadratic program, the distributional geometry of massive uncertain data can be effectively captured as a compact convex uncertainty set, which considerably reduces conservatism of robust optimization problems. The induced robust counterpart problem retains the … Read more