Nonlinear Optimization

On Stationary Conditions and the Convergence of Augmented Lagrangian methods for Generalized Nash Equilibrium Problems

  • Lennin Mallma Ramirez
  • Frank Navarro Rojas
  • Alberto Ramos
    • Categories Constrained Nonlinear Optimization, Game Theory, Nonlinear Optimization Tags , , , ,

    In this work, we study stationarity conditions and constraint qualifications (CQs) tailored to Generalized Nash Equilibrium Problems (GNEPs) and analyze their relationships and implications for the global convergence of algorithms. We recall that GNEPs generalize Nash Equilibrium Problems (NEPs) in that the feasible strategy set of each player depends on the strategies chosen by the … Read more

    A Multi-Secant Limited-Memory BFGS Method

  • Fedor V. Gubarev
    • Categories Unconstrained Optimization Tags ,

    We develop multi-secant BFGS-like quasi-Newton updating scheme, which adaptively selects the number of imposed secant conditions and naturally preserves positivity of approximated Hessian. Compact representation and respective limited-memory formulation are also derived. Numerical stability is assured via unconventional damping technique, which symmetrically handles coordinate and gradient differences. Practical relevance of proposed method is demonstrated via … Read more

    A Modified Projected Gradient Algorithm for Solving Quasiconvex Programming with Applications

  • Pham Thi Hoai
    • Categories Constrained Nonlinear Optimization, Convex Optimization, Nonlinear Optimization Tags , , , ,

    In this manuscript, we introduce a novel projected gradient algorithm for solving quasiconvex optimization problems over closed convex sets. The key innovation of our new algorithm is an adaptive, parameter-free stepsize rule that requires no line search and avoids estimating constants, such as Lipschitz modulus. Unlike recent self-adaptive approach given in [17] which typically produce … Read more

    Negative Curvature Methods with High-Probability Complexity Guarantees for Stochastic Nonconvex Optimization

  • Albert S. Berahas
  • Raghu Bollapragada
  • Wanping Dong
    • Categories Nonlinear Optimization, Unconstrained Optimization Tags , ,

    This paper develops negative curvature methods for continuous nonlinear unconstrained optimization in stochastic settings, in which function, gradient, and Hessian information is available only through probabilistic oracles, i.e., oracles that return approximations of a certain accuracy and reliability. We introduce conditions on these oracles and design a two-step framework that systematically combines gradient and negative … Read more

    Efficient Warm-Start Strategies for Nash-based Linear Complementarity Problems via Bilinear Approximation

  • Dominic C. Flocco
  • Steven A. Gabriel
    • Categories Complementarity and Variational Inequalities, Constrained Nonlinear Optimization, Global Optimization Applications Tags , , ,

    We present an effective warm-starting scheme for solving large linear complementarity problems (LCPs) arising from Nash equilibrium problems. The approach generates high-quality starting points that, when passed to the PATH solver, yield substantial reductions in computational time and variance. Our warm-start routine reformulates each agent’s LP using strong duality, leading to a master problem with … Read more

    Modeling Binary Relations in Piecewise-Linear Approximations

  • Kristin Braun
  • Robert Burlacu
  • Tobias Kuen
  • Kristina Rolsing
    • Categories Combinatorial Optimization, Global Optimization Theory, Nonlinear Optimization Tags , , , , ,

    Over the last decades, using piecewise-linear mixed-integer relaxations of nonlinear expressions has become a strong alternative to spatial branching for solving mixed-integer nonlinear programs. Since these relaxations give rise to large numbers of binary variables that encode interval selections, strengthening them is crucial. We investigate how to exploit the resulting combinatorial structure by integrating cutting-plane … Read more

    A Projected Stochastic Gradient Method for Finite-Sum Problems with Linear Equality Constraints

  • Nataša Krklec Jerinkić
  • Benedetta Morini
  • Mahsa Yousefi
    • Categories Nonlinear Optimization, Optimization in Data Science Tags , ,

    A stochastic gradient method for finite-sum minimization subject to deterministic linear constraints is proposed and analyzed. The procedure presented adapts the projected gradient method on a convex set to the use of both a stochastic gradient and a possibly inexact projection map. Under standard assumptions in the field of stochastic gradient methods, we provide theoretical … Read more

    Improved Analysis of Restarted Accelerated Gradient and Augmented Lagrangian Methods via Inexact Proximal Point Frameworks

  • Matthew X. Burns
  • Jiaming Liang
    • Categories Constrained Nonlinear Optimization, Convex and Nonsmooth Optimization, Convex Optimization Tags , , , ,

    This paper studies a class of double-loop (inner-outer) algorithms for convex composite optimization. For unconstrained problems, we develop a restarted accelerated composite gradient method that attains the optimal first-order complexity in both the convex and strongly convex settings. For linearly constrained problems, we introduce inexact augmented Lagrangian methods, including a basic method and an outer-accelerated … Read more

    Modelling and Analysis of an Inverse Parameter Identification Problem in Piezoelectricity

  • Raphael Kuess
  • Daniel Walter
  • Andrea Walther
    • Categories Infinite Dimensional Optimization, Nonlinear Systems and Least-Squares, Systems governed by Differential Equations Optimization Tags , , , , ,

    Piezoelectric material behavior is mathematically described by coupled hyperbolic-elliptic partial differential equations (PDEs) governing mechanical displacement and electrical potential. This paper presents advancements in the theory of identifying material parameters in piezoelectric PDEs. We focus on modeling and analyzing the inverse problem assuming matrix-valued Sobolev-Bochner parameters to encompass a time and space-dependent setting and thus … Read more

    A General Penalty-Method and a General Regularization-Method for Cardinality-Constrained Optimization Problems

  • Felix P. Broesamle
    • Categories Complementarity and Variational Inequalities, Constrained Nonlinear Optimization, Nonlinear Optimization Tags , , , , ,

    We consider cardinality-constrained optimization problems (CCOPs), which are general nonlinear programs with an additional constraint limiting the number of nonzero continuous variables. The continuous reformulation of CCOPs involves complementarity constraints, which pose significant theoretical and computational challenges. To address these difficulties, we propose and analyze two numerical solution approaches: a general penalty method and a … Read more