Applications – Science and Engineering

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

    Sparse Poisson regression via mixed-integer optimization

  • Kota Kudo
  • Yuichi Takano
  • Hiroki Saishu
    • Categories Integer Programming, Statistics Tags , , ,

    We present a mixed-integer optimization (MIO) approach to sparse Poisson regression. The MIO approach to sparse linear regression was first proposed in the 1970s, but has recently received renewed attention due to advances in optimization algorithms and computer hardware. In contrast to many sparse estimation algorithms, the MIO approach has the advantage of finding the … Read more

    Exterior-point Optimization for Nonconvex Learning

  • Shuvomoy Das Gupta
  • Bartolomeo Stellato
  • Bart Paul Gerard Van Parys
    • Categories Constrained Nonlinear Optimization, Nonsmooth Optimization, Statistics Tags , , ,

    In this paper we present the nonconvex exterior-point optimization solver (NExOS)—a novel first-order algorithm tailored to constrained nonconvex learning problems. We consider the problem of minimizing a convex function over nonconvex constraints, where the projection onto the constraint set is single-valued around local minima. A wide range of nonconvex learning problems have this structure including … Read more

    Graph Recovery From Incomplete Moment Information

  • Didier Henrion
  • Jean-Bernard Lasserre
    • Categories Infinite Dimensional Optimization, Semi-definite Programming, Statistics Tags , , ,

    We investigate a class of moment problems, namely recovering a measure supported on the graph of a function from partial knowledge of its moments, as for instance in some problems of optimal transport or density estimation. We show that the sole knowledge of first degree moments of the function, namely linear measurements, is sufficient to … Read more

    Failure Probability Constrained AC Optimal Power Flow

  • Mihai Anitescu
  • Anirudh Subramanyam
  • Jacob Roth
    • Categories Energy, Nonlinear Optimization Tags ,

    Despite cascading failures being the central cause of blackouts in power transmission systems, existing operational and planning decisions are made largely by ignoring their underlying cascade potential. This paper posits a reliability-aware AC Optimal Power Flow formulation that seeks to design a dispatch point which has a low operator-specified likelihood of triggering a cascade starting … Read more