Applications – Science and Engineering

Optimization with learning-informed differential equation constraints and its applications

  • Guozhi Dong
  • Michael Hintermueller
  • Kostas Papafitsoros
    • Categories Biomedical Applications, Infinite Dimensional Optimization, Nonlinear Optimization

    Inspired by applications in optimal control of semilinear elliptic partial differential equations and physics-integrated imaging, differential equation constrained optimization problems with constituents that are only accessible through data-driven techniques are studied. A particular focus is on the analysis and on numerical methods for problems with machine-learned components. For a rather general context, an error analysis … Read more

    Unbiased Subdata Selection for Fair Classification: A Unified Framework and Scalable Algorithms

  • Ye Qing
  • Weijun Xie
    • Categories (Mixed) Integer Nonlinear Programming, Data-Mining

    As an important problem in modern data analytics, classification has witnessed varieties of applications from different domains. Different from conventional classification approaches, fair classification concerns the issues of unintentional biases against the sensitive features (e.g., gender, race). Due to high nonconvexity of fairness measures, existing methods are often unable to model exact fairness, which can … Read more

    Kernel Distributionally Robust Optimization

  • Moritz Diehl
  • Wittawat Jitkrittum
  • Bernhard Schölkopf
  • Jia-Jie Zhu
    • Categories Robust Optimization, Statistics, Stochastic Programming Tags , , ,

    We propose kernel distributionally robust optimization (Kernel DRO) using insights from the robust optimization theory and functional analysis. Our method uses reproducing kernel Hilbert spaces (RKHS) to construct a wide range of convex ambiguity sets, including sets based on integral probability metrics and finite-order moment bounds. This perspective unifies multiple existing robust and stochastic optimization … Read more

    A dynamic programming approach to segmented isotonic regression

  • Victor Bucarey
  • Martine Labbé
  • Juan M. Morales
  • Salvador Pineda
    • Categories Data-Mining, Dynamic Programming, Energy Tags , , , , ,

    This paper proposes a polynomial-time algorithm to construct the monotone stepwise curve that minimizes the sum of squared errors with respect to a given cloud of data points. The fitted curve is also constrained on the maximum number of steps it can be composed of and on the minimum step length. Our algorithm relies on … Read more

    Algorithms for Block Tridiagonal Systems: Foundations and New Results for Generalized Kalman Smoothing

  • Aleksandr Y. Aravkin
  • James V. Burke
  • Bradley Bell
  • Gianluigi Pillonetto
    • Categories Control Applications, Convex Optimization

    Block tridiagonal systems appear in classic Kalman smoothing problems, as well in generalized Kalman smoothing, where problems may have nonsmooth terms, singular covariance, constraints, nonlinear models, and unknown parameters. In this paper, first we interpret all the classic smoothing algorithms as different approaches to solve positive definite block tridiagonal linear systems. Then, we obtain new … Read more

    Safely Learning Dynamical Systems from Short Trajectories

  • Amir Ali Ahmadi
  • Abraar Chaudhry
  • Vikas Sindhwani
  • Stephen Tu
    • Categories Control Applications, Linear, Cone and Semidefinite Programming, Robust Optimization Tags , , , ,

    A fundamental challenge in learning to control an unknown dynamical system is to reduce model uncertainty by making measurements while maintaining safety. In this work, we formulate a mathematical definition of what it means to safely learn a dynamical system by sequentially deciding where to initialize the next trajectory. In our framework, the state of … Read more

    An Alternating Method for Cardinality-Constrained Optimization: A Computational Study for the Best Subset Selection and Sparse Portfolio Problems

  • Carina Moreira Costa
  • Dennis Kreber
  • Martin Schmidt
    • Categories (Mixed) Integer Nonlinear Programming, Finance and Economics, Statistics Tags , , , ,

    Cardinality-constrained optimization problems are notoriously hard to solve both in theory and practice. However, as famous examples such as the sparse portfolio optimization and best subset selection problems show, this class is extremely important in real-world applications. In this paper, we apply a penalty alternating direction method to these problems. The key idea is to … Read more

    Affine Decision Rule Approximation to Immunize against Demand Response Uncertainty in Smart Grids’ Capacity Planning

  • Sajad Aliakbari-Sani
  • Olivier Bahn
  • Erick Delage
    • Categories Energy, Linear Programming, Robust Optimization Tags , , ,

    Generation expansion planning (GEP) is a classical problem that determines an optimal investment plan for existing and future electricity generation technologies. GEP is a computationally challenging problem, as it typically corresponds to a very large-scale problem that contains several sources of uncertainties. With the advent of demand response (DR) as a reserved capacity in modern … Read more

    Decentralized Failure-Tolerant Optimization of Electric Vehicle Charging

  • Ignacio Aravena
  • Steve Chaping
  • Colin Ponce
    • Categories Convex Optimization, Energy, Scheduling Tags , , ,

    We present a decentralized failure-tolerant algorithm for optimizing electric vehicle (EV) charging, using charging stations as computing agents. The algorithm is based on the alternating direction method of multipliers (ADMM) and it has the following features: (i) It handles capacity, peak demand, and ancillary services coupling constraints. (ii) It does not require a central agent … Read more

    A study of the relation between the single-row and the double-row facility layout problem

  • Mirko Dahlbeck
  • Anja Fischer
  • Philipp Hungerländer
    • Categories (Mixed) Integer Linear Programming, Applications - OR and Management Sciences, Facility Planning and Design Tags , ,

    The NP-hard Multi-Row Facility Layout Problem (MRFLP) consists of a set of one-dimensional departments and pairwise transport weights between them. It asks for a non-overlapping arrangement of the departments along a given number of rows such that the weighted sum of the horizontal center-to-center distances between the departments is minimized. We mainly focus on the … Read more