Infinite Dimensional Optimization

On regularized structure exploiting Quasi-Newton methods for ill-posed problems

  • Raphael Kuess
  • Andrea Walther
    • Categories Infinite Dimensional Optimization, Nonlinear Systems and Least-Squares Tags , , , ,

    Inverse problems are inherently ill-posed, leading standard optimization techniques to fail and necessitating the use of regularization. This paper introduces a regularized, structure-exploiting Powell-Symmetric-Broyden method under modified secant conditions for solving ill-posed inverse problems in both infinite dimensional and finite dimensional settings. Our approach integrates regularization and structure exploitation directly within the Quasi-Newton framework, leveraging … Read more

    Optimal Control of Semilinear Graphon Systems

  • Martin T. Köhler
  • Artemi Makarow
  • Christian Kirches
    • Categories Infinite Dimensional Optimization, Network Optimization, Systems governed by Differential Equations Optimization Tags , , ,

    Controlling the dynamics of large-scale networks is essential for a macroscopic reduction of overall consumption and losses in the context of energy supply, finance, logistics, and mobility. We investigate the optimal control of semilinear dynamical systems on asymptotically infinite networks, using the notion of graphons. Graphons represent a limit object of a converging graph sequence … Read more

    Two-Stage Distributionally Robust Optimization: Intuitive Understanding and Algorithm Development from the Primal Perspective

  • Zhengsong Lu
  • Bo Zeng
    • Categories Robust Optimization, Semi-infinite Programming Tags , ,

    In this paper, we study the two-stage distributionally robust optimization (DRO) problem from the primal perspective. Unlike existing approaches, this perspective allows us to build a deeper and more intuitive understanding on DRO, to leverage classical and well established solution methods and to develop a general and fast decomposition algorithm (and its variants), and to … Read more

    Distributionally Robust Optimization

  • Daniel Kuhn
  • Soroosh Shafiee
  • Wolfram Wiesemann
    • Categories Robust Optimization, Semi-infinite Programming, Stochastic Programming Tags , , ,

    Distributionally robust optimization (DRO) studies decision problems under uncertainty where the probability distribution governing the uncertain problem parameters is itself uncertain. A key component of any DRO model is its ambiguity set, that is, a family of probability distributions consistent with any available structural or statistical information. DRO seeks decisions that perform best under the … Read more

    The Blessing of Strategic Customers in Personalized Pricing

  • Zhi Chen
  • Bradley Sturt
  • Weijun Xie
    • Categories Infinite Dimensional Optimization, Robust Optimization, Stochastic Programming

    We consider a feature-based personalized pricing problem in which the buyer is strategic: given the seller’s pricing policy, the buyer can augment the features that they reveal to the seller to obtain a low price for the product. We model the seller’s pricing problem as a stochastic program over an infinite-dimensional space of pricing policies … Read more

    The best approximation pair problem relative to two subsets in a normed space

  • Daniel Reem
  • Yair Censor
    • Categories Convex and Nonsmooth Optimization, Global Optimization, Infinite Dimensional Optimization Tags , , , , , , , , ,

    In the classical best approximation pair (BAP) problem, one is given two nonempty, closed, convex and disjoint subsets in a finite- or an infinite-dimensional Hilbert space, and the goal is to find a pair of points, each from each subset, which realizes the distance between the subsets. This problem, which has a long history, has … Read more

    Frequency regulation with storage: On losses and profits

  • Dirk Lauinger
  • François Vuille
  • Daniel Kuhn
    • Categories Energy, Robust Optimization, Semi-infinite Programming Tags , , , , , ,

    Low-carbon societies will need to store vast amounts of electricity to balance intermittent generation from wind and solar energy, for example, through frequency regulation. Here, we derive an analytical solution to the decision-making problem of storage operators who sell frequency regulation power to grid operators and trade electricity on day-ahead markets. Mathematically, we treat future … Read more

    Solving moment and polynomial optimization problems on Sobolev spaces

  • Didier Henrion
  • Alessandro Rudi
    • Categories Global Optimization, Infinite Dimensional Optimization, Semi-definite Programming Tags , , ,

    Using standard tools of harmonic analysis, we state and solve the problem of moments for positive measures supported on the unit ball of a Sobolev space of multivariate periodic trigonometric functions. We describe outer and inner semidefinite approximations of the cone of Sobolev moments. They are the basic components of an infinite-dimensional moment-sums of squares … Read more

    libDIPS — Discretization-Based Semi-Infinite and Bilevel Programming Solvers

  • Aron Zingler
  • Alexander Mitsos
  • Daniel Jungen
  • Hatim Djelassi
    • Categories Optimization Software and Modeling Systems, Robust Optimization, Semi-infinite Programming Tags , , , , ,

    We consider several hierarchical optimization programs: (generalized) semi-infinite and existence-constrained semi-infinite programs, minmax, and bilevel programs. Multiple adaptive discretization-based algorithms have been published for these program classes in recent decades. However, rigorous numerical performance comparisons between these algorithms are lacking. Indeed, if numerical comparisons are provided at all, they usually compare a small selection of … Read more

    Local Convergence Analysis of an Inexact Trust-Region Method for Nonsmooth Optimization

  • Robert Baraldi
  • Drew P. Kouri
    • Categories Infinite Dimensional Optimization, Nonlinear Optimization, Nonsmooth Optimization Tags , , , , ,

    In [R. J. Baraldi and D. P. Kouri, Mathematical Programming, (2022), pp. 1–40], we introduced an inexact trust-region algorithm for minimizing the sum of a smooth nonconvex function and a nonsmooth convex function in Hilbert space—a class of problems that is ubiquitous in data science, learning, optimal control, and inverse problems. This algorithm has demonstrated … Read more