Nonlinear Optimization

Worst-case convergence analysis of gradient and Newton methods through semidefinite programming performance estimation

  • Etienne de Klerk
  • François Glineur
  • Adrien B. Taylor
    • Categories Linear, Cone and Semidefinite Programming, Nonlinear Optimization Tags , , ,

    We provide new tools for worst-case performance analysis of the gradient (or steepest descent) method of Cauchy for smooth strongly convex functions, and Newton’s method for self-concordant functions. The analysis uses semidefinite programming performance estimation, as pioneered by Drori en Teboulle [Mathematical Programming, 145(1-2):451–482, 2014], and extends recent performance estimation results for the method of … Read more

    Inner Conditions for Error Bounds and Metric Subregulerity of Multifunctions

  • Dominique Azé
    • Categories Convex and Nonsmooth Optimization, Generalized Convexity/Monoticity, Nonlinear Optimization Tags , , , , ,

    We introduce a new class of sets, functions and multifunctions which is shown to be large and to enjoy some nice common properties with the convex setting. Error bounds for objects attached to this class are characterized in terms of inner conditions of Abadie’s type, that is conditions bearing on normal cones and coderivatives at … Read more

    Iteratively Linearized Reweighted Alternating Direction Method of Multipliers for a Class of Nonconvex Problems

  • Jiang Hao
  • Cheng Lizhi
  • Sun Tao
    • Categories Nonlinear Optimization

    In this paper, we consider solving a class of nonconvex and nonsmooth problems frequently appearing in signal processing and machine learning research. The traditional alternating direction method of multipliers encounters troubles in both mathematics and computations in solving the nonconvex and nonsmooth subproblem. In view of this, we propose a reweighted alternating direction method of … Read more

    Convergence Analysis of Processes with Valiant Projection Operators in Hilbert Space

  • Yair Censor
  • Rafiq Mansour
    • Categories Constrained Nonlinear Optimization, Convex Optimization

    Convex feasibility problems require to find a point in the intersection of a finite family of convex sets. We propose to solve such problems by performing set-enlargements and applying a new kind of projection operators called valiant projectors. A valiant projector onto a convex set implements a special relaxation strategy, proposed by Goffin in 1971, … Read more

    Complementarity-Based Nonlinear Programming Techniques for Optimal Mixing in Gas Networks

  • Falk M. Hante
  • Martin Schmidt
    • Categories Applications - Science and Engineering, Complementarity and Variational Inequalities, Nonlinear Optimization Tags , , , ,

    We consider nonlinear and nonsmooth mixing aspects in gas transport optimization problems. As mixed-integer reformulations of pooling-type mixing models already render small-size instances computationally intractable, we investigate the applicability of smooth nonlinear programming techniques for equivalent complementarity-based reformulations. Based on recent results for remodeling piecewise affine constraints using an inverse parametric quadratic programming approach, we … Read more

    A General Regularized Continuous Formulation for the Maximum Clique Problem

  • James T. Hungerford
  • Francesco Rinaldi
    • Categories Combinatorial Optimization, Network Optimization, Nonlinear Optimization Tags , , , ,

    In this paper, we develop a general regularization-based continuous optimization framework for the maximum clique problem. In particular, we consider a broad class of regularization terms that can be included in the classic Motzkin-Strauss formulation and we develop conditions that guarantee the equivalence between the continuous regularized problem and the original one in both a … Read more

    A sequential optimality condition related to the quasinormality constraint qualification and its algorithmic consequences

  • Roberto Andreani
  • N. S. Fazzio
  • María Laura Schuverdt
  • Leonardo D. Secchin
    • Categories Constrained Nonlinear Optimization Tags , , ,

    In the present paper, we prove that the augmented Lagrangian method converges to KKT points under the quasinormality constraint qualification, which is associated with the external penalty theory. For this purpose, a new sequential optimality condition for smooth constrained optimization, called PAKKT, is defined. The new condition takes into account the sign of the dual … Read more

    Planar Maximum Coverage Location Problem with Partial Coverage and General Spatial Representation of Demand and Service Zones

  • Manish Bansal
    • Categories Approximation Algorithms, Nonlinear Optimization, Production and Logistics

    We introduce a new generalization of the classical planar maximum coverage location problem (PMCLP) in which demand zones and service zone of each facility are represented by spatial objects such as circles, polygons, etc., and are allowed to be located anywhere in a continuous plane. In addition, we allow partial coverage in its true sense, … Read more

    On Affine Invariant Descent Directions

  • Yu-Hong Dai
  • Florian Jarre
  • Felix Lieder
    • Categories Nonlinear Optimization Tags , ,

    This paper explores the existence of affine invariant descent directions for unconstrained minimization. While there may exist several affine invariant descent directions for smooth functions $f$ at a given point, it is shown that for quadratic functions there exists exactly one invariant descent direction in the strictly convex case and generally none in the nondegenerate … Read more

    Portfolio Optimization with Entropic Value-at-Risk

  • Ahmadi-Javid Amir
  • Fallah-Tafti Malihe
    • Categories Constrained Nonlinear Optimization, Finance and Economics, Stochastic Programming

    The entropic value-at-risk (EVaR) is a new coherent risk measure, which is an upper bound for both the value-at-risk (VaR) and conditional value-at-risk (CVaR). As important properties, the EVaR is strongly monotone over its domain and strictly monotone over a broad sub-domain including all continuous distributions, while well-known monotone risk measures, such as VaR and … Read more