Sensitivity-informed identification of temperature-dependent piezoelectric material parameters

  • Raphael Kuess
  • Olga Friesen
  • Leander Claes
  • Andrea Walther
    • Categories Applications - Science and Engineering, Control Applications, Nonlinear Optimization Tags , , ,

    An accurate characterization of temperature-dependent material parameters of piezoceramics is crucial for the design and simulation of reliable sensors and actuators. This characterization is typically formulated as an ill-posed inverse problem, which is challenging to solve not only because of its ill-posedness, but also because of parameter sensitivities, which vary by several orders of magnitude … Read more

    Convex analysis for composite functions without K-convexity

  • Juan Pablo Vielma
    • Categories Convex Optimization, Generalized Convexity/Monoticity

    Composite functions have been studied for over 40 years and appear in a wide range of optimization problems. Convex analysis of these functions focuses on (i) conditions for convexity of the function based on properties of its components, (ii) formulas for the convex conjugate of the function based on those of its components and (iii) … Read more

    Convex duality contracts for production-grade mathematical optimization

  • Juan Pablo Vielma
  • Ross Anderson
  • Joey Huchette
    • Categories Convex Optimization, Linear, Cone and Semidefinite Programming, Modeling Languages and Systems

    Deploying mathematical optimization in autonomous production systems requires precise contracts for objects returned by an optimization solver. Unfortunately, conventions on dual solution and infeasibility certificates (rays) vary widely across solvers and classes of problems. This paper presents the theoretical framework used by MathOpt (a domain-specific language developed and used at Google) to unify these notions. … Read more

    Riemannian Dueling Optimization

  • Yuxuan Ren
  • Abhishek Roy
  • Shiqian Ma
    • Categories Nonlinear Optimization Tags , , ,

    Dueling optimization considers optimizing an objective with access to only a comparison oracle of the objective function. It finds important applications in emerging fields such as recommendation systems and robotics. Existing works on dueling optimization mainly focused on unconstrained problems in the Euclidean space. In this work, we study dueling optimization over Riemannian manifolds, which … Read more

    A simulation framework for Formula 1 race strategy based on pit-stop optimization

  • Mario Borruso
  • Pasquale Avella
    • Categories (Mixed) Integer Linear Programming, Linear Programming, Optimization Software and Modeling Systems Tags , , , ,

    In modern Formula~1, strict regulations and highly optimized cars limit performance gains through hardware, increasing the importance of strategic decision-making. This work tackles the problem of computing a race strategy that minimizes total race time by jointly optimizing tire stints, compound selection, fuel load, and Energy Recovery System (ERS) deployment. We present a high-performance simulation … Read more

    An objective-function-free algorithm for general smooth constrained optimization

  • Stefania Bellavia
  • Serge Gratton
  • Benedetta Morini
  • Philippe L. Toint
    • Categories Constrained Nonlinear Optimization, Nonlinear Optimization Tags , ,

    A new algorithm for smooth constrained optimization is proposed that never computes the value of the problem’s objective function and that handles both equality and inequality constraints. The algorithm uses an adaptive switching strategy between a normal step aiming at reducing constraint’s infeasibility and a tangential step improving dual optimality, the latter being inspired by … Read more

    Revisiting Superlinear Convergence of Proximal Newton-Like Methods to Degenerate Solutions

  • Ching-pei Lee
  • Stephen Wright
    • Categories Nonsmooth Optimization Tags , , , , ,

    We describe inexact proximal Newton-like methods for solving degenerate regularized optimization problems and for the broader problem of finding a zero of a generalized equation that is the sum of a continuous map and a maximal monotone operator. Superlinear convergence for both the distance to the solution set and a certain measure of first-order optimality … Read more

    Learning to Choose Branching Rules for Nonconvex MINLPs

  • Timo Berthold
  • Fritz Geis
    • Categories Constrained Nonlinear Optimization, Nonlinear Optimization

    Outer-approximation-based branch-and-bound is a common algorithmic framework for solving MINLPs (mixed-integer nonlinear programs) to global optimality, with branching variable selection critically influencing overall performance. In modern global MINLP solvers, it is unclear whether branching on fractional integer variables should be prioritized over spatial branching on variables, potentially continuous, that show constraint violations, with different solvers … Read more

    Linear Model Extraction via Factual and Counterfactual Queries

  • Daan Otto
  • Jannis Kurtz
  • Dick den Hertog
  • Ş. İlker Birbil
    • Categories Data Science Algorithms, Data Science Theory, Optimization in Data Science Tags , ,

    In model extraction attacks, the goal is to reveal the parameters of a black-box machine learning model by querying the model for a selected set of data points. Due to an increasing demand for explanations, this may involve counterfactual queries besides the typically considered factual queries. In this work, we consider linear models and three … Read more

    Exact and Heuristic Methods for Gamma-Robust Min-Max Problems

  • Yasmine Beck
    • Categories Bilevel Optimization, Combinatorial Optimization, Robust Optimization

    Bilevel optimization is a powerful tool for modeling hierarchical decision-making processes, which arise in various real-world applications. Due to their nested structure, however, bilevel problems are intrinsically hard to solve—even if all variables are continuous and all parameters of the problem are exactly known. Further challenges arise if mixed-integer aspects and problems under uncertainty are … Read more