Nonlinear Optimization

A Personalized Switched Systems Approach for the Optimal Control of Ventricular Assist Devices based on Atrioventricular Plane Displacement

  • Rüdiger C. Braun-Dullaeus
  • Sebastian Sager
  • Jeremi Kaj Mizerski
  • Thomas Rauwolf
  • Alexander Schmeisser
  • Clemens Zeile
    • Categories Biomedical Applications, Control Applications, Systems governed by Differential Equations Optimization Tags , , ,

    Objective: A promising treatment for congestive heart failure is the implementation of a left ventricular assist device (LVAD) that works as a mechanical pump. Modern LVADs work with adjustable constant rotor speed and provide therefore continuous blood flow; however, recently undertaken efforts try to mimic pulsatile blood flow by oscillating the pump speed. This work … Read more

    Riemannian conjugate gradient methods with inverse retraction

  • Hiroyuki Sato
  • Xiaojing Zhu
    • Categories Nonlinear Optimization Tags , , , , ,

    We propose a new class of Riemannian conjugate gradient (CG) methods, in which inverse retraction is used instead of vector transport for search direction construction. In existing methods, differentiated retraction is often used for vector transport to move the previous search direction to the current tangent space. However, a different perspective is adopted here, motivated … Read more

    Two novel gradient methods with optimal step sizes

  • Oscar S. Dalmau
  • Rafael Herrera
  • Harry Oviedo
    • Categories Convex Optimization, Nonlinear Optimization Tags , , ,

    In this work we introduce two new Barzilai and Borwein-like steps sizes for the classical gradient method for strictly convex quadratic optimization problems. The proposed step sizes employ second-order information in order to obtain faster gradient-type methods. Both step sizes are derived from two unconstrained optimization models that involve approximate information of the Hessian of … Read more

    Solving nonlinear systems of equations via spectral residual methods: stepsize selection and applications

  • Enrico Meli
  • Benedetta Morini
  • Margherita Porcelli
  • Cristina Sgattoni
    • Categories Mechanical Engineering, Nonlinear Systems and Least-Squares

    Spectral residual methods are derivative-free and low-cost per iteration procedures for solving nonlinear systems of equations. They are generally coupled with a nonmonotone linesearch strategy and compare well with Newton-based methods for large nonlinear systems and sequences of nonlinear systems. The residual vector is used as the search direction and choosing the steplength has a … Read more

    High-order Evaluation Complexity of a Stochastic Adaptive Regularization Algorithm for Nonconvex Optimization Using Inexact Function Evaluations and Randomly Perturbed Derivatives

  • Stefania Bellavia
  • Benedetta Morini
  • Philippe L. Toint
  • Gianmarco Gurioli
    • Categories Bound-constrained Optimization, Constrained Nonlinear Optimization, Unconstrained Optimization Tags , , ,

    A stochastic adaptive regularization algorithm allowing random noise in derivatives and inexact function values is proposed for computing strong approximate minimizers of any order for inexpensively constrained smooth optimization problems. For an objective function with Lipschitz continuous p-th derivative in a convex neighbourhood of the feasible set and given an arbitrary optimality order q, it … Read more

    A derivative-free method for structured optimization problems

  • Andrea Cristofari
  • Francesco Rinaldi
    • Categories Nonlinear Optimization

    Structured optimization problems are ubiquitous in fields like data science and engineering. The goal in structured optimization is using a prescribed set of points, called atoms, to build up a solution that minimizes or maximizes a given function. In the present paper, we want to minimize a black-box function over the convex hull of a … Read more

    On the use of Jordan Algebras for improving global convergence of an Augmented Lagrangian method in nonlinear semidefinite programming

  • Roberto Andreani
  • Ellen H. Fukuda
  • Gabriel Haeser
  • Daiana O. Santos
  • Leonardo D. Secchin
    • Categories Nonlinear Optimization, Semi-definite Programming Tags , , , ,

    Jordan Algebras are an important tool for dealing with semidefinite programming and optimization over symmetric cones in general. In this paper, a judicious use of Jordan Algebras in the context of sequential optimality conditions is done in order to generalize the global convergence theory of an Augmented Lagrangian method for nonlinear semidefinite programming. An approximate … Read more

    A Primal–Dual Penalty Method via Rounded Weighted-\boldmath{$\ell_1$} Lagrangian Duality

  • Regina S. Burachik
  • Christopher J. Price
  • C. Yalcin Kaya
    • Categories Constrained Nonlinear Optimization, Nonlinear Optimization

    We propose a new duality scheme based on a sequence of smooth minorants of the weighted-$\ell_1$ penalty function, interpreted as a parametrized sequence of augmented Lagrangians, to solve nonconvex and nonsmooth constrained optimization problems. For the induced sequence of dual problems, we establish strong asymptotic duality properties. Namely, we show that (i) the sequence of … Read more

    On Inexact Accelerated Proximal Gradient Methods with Relative Error Rules

  • Yunier Bello-Cruz
  • Max L. N. Gonçalves
  • Nathan Krislock
    • Categories Convex and Nonsmooth Optimization, Nonlinear Optimization Tags , , , , ,

    One of the most popular and important first-order iterations that provides optimal complexity of the classical proximal gradient method (PGM) is the “Fast Iterative Shrinkage/Thresholding Algorithm” (FISTA). In this paper, two inexact versions of FISTA for minimizing the sum of two convex functions are studied. The proposed schemes inexactly solve their subproblems by using relative … Read more

    Iteration-complexity of an inexact proximal accelerated augmented Lagrangian method for solving linearly constrained smooth nonconvex composite optimization problems

  • Jefferson Gonçalves Melo
  • Renato D.C. Monteiro
  • Hairong Wang
    • Categories Constrained Nonlinear Optimization Tags , , ,

    This paper proposes and establishes the iteration-complexity of an inexact proximal accelerated augmented Lagrangian (IPAAL) method for solving linearly constrained smooth nonconvex composite optimization problems. Each IPAAL iteration consists of inexactly solving a proximal augmented Lagrangian subproblem by an accelerated composite gradient (ACG) method followed by a suitable Lagrange multiplier update. It is shown that … Read more