Serge Gratton

Conjugate-gradients versus multigrid solvers for diffusion-based correlation models in data assimilation

  • Serge Gratton
  • Philippe L. Toint
  • Jean Tshimanga Ilunga
    • Categories Nonlinear Systems and Least-Squares, Optimization of Systems modeled by PDEs

    This paper provides a theoretical and experimental comparison between conjugate-gradients and multigrid, two iterative schemes for solving linear systems, in the context of applying diffusion-based correlation models in data assimilation. In this context, a large number of such systems has to be (approximately) solved if the implicit mode is chosen for integrating the involved diffusion … Read more

    Globally Convergent Evolution Strategies and CMA-ES

  • Youssef Diouane
  • Serge Gratton
  • Luis Nunes Vicente
    • Categories Unconstrained Optimization Tags , , ,

    In this paper we show how to modify a large class of evolution strategies (ES) to rigorously achieve a form of global convergence, meaning convergence to stationary points independently of the starting point. The type of ES under consideration recombine the parents by means of a weighted sum, around which the offsprings are computed by … Read more

    A surrogate management framework using rigorous trust-regions steps

  • Serge Gratton
  • Luis Nunes Vicente
    • Categories Applications - Science and Engineering, Nonlinear Optimization, Optimization of Simulated Systems Tags , , ,

    Surrogate models and heuristics are frequently used in the optimization engineering community as convenient approaches to deal with functions for which evaluations are expensive or noisy, or lack convexity. These methodologies do not typically guarantee any type of convergence under reasonable assumptions and frequently render slow convergence. In this paper we will show how to … Read more

    A surrogate management framework using rigorous trust-regions steps

  • Serge Gratton
    • Categories Applications - Science and Engineering, Nonlinear Optimization, Optimization of Simulated Systems Tags , , ,

    Surrogate models and heuristics are frequently used in the optimization engineering community as convenient approaches to deal with functions for which evaluations are expensive or noisy, or lack convexity. These methodologies do not typically guarantee any type of convergence under reasonable assumptions and frequently render slow convergence. In this paper we will show how to … Read more

    Preconditioning and Globalizing Conjugate Gradients in Dual Space for Quadratically Penalized Nonlinear-Least Squares Problems

  • Serge Gratton
  • Philippe L. Toint
  • Selime Gürol
    • Categories Nonlinear Systems and Least-Squares, Optimization of Simulated Systems, Optimization of Systems modeled by PDEs Tags , , , , ,

    When solving nonlinear least-squares problems, it is often useful to regularize the problem using a quadratic term, a practice which is especially common in applications arising in inverse calculations. A solution method derived from a trust-region Gauss-Newton algorithm is analyzed for such applications, where, contrary to the standard algorithm, the least-squares subproblem solved at each … Read more

    Using approximate secant equations in limited memory methods for multilevel unconstrained optimization

  • Serge Gratton
  • Vincent Malmedy
  • Philippe L. Toint
    • Categories Optimization of Systems modeled by PDEs, Unconstrained Optimization Tags , , , ,

    The properties of multilevel optimization problems defined on a hierarchy of discretization grids can be used to define approximate secant equations, which describe the second-order behaviour of the objective function. Following earlier work by Gratton and Toint (2009), we introduce a quasi-Newton method (with a linesearch) and a nonlinear conjugate gradient method that both take … Read more

    Stopping rules and backward error analysis for bound-constrained optimization

  • Serge Gratton
  • Philippe L. Toint
  • Mélodie Mouffe
    • Categories Bound-constrained Optimization, Optimization Software Design Principles Tags , , , ,

    Termination criteria for the iterative solution of bound-constrained optimization problems are examined in the light of backward error analysis. It is shown that the problem of determining a suitable perturbation on the problem’s data corresponding to the definition of the backward error is analytically solvable under mild assumptions. Moreover, a link between existing termination criteria … Read more

    On a class of limited memory preconditioners for large scale linear systems with multiple right-hand sides

  • Serge Gratton
  • Annick Sartenaer
  • Jean Tshimanga Ilunga
    • Categories Nonlinear Optimization, Nonlinear Systems and Least-Squares Tags , , ,

    This work is concerned with the development and study of a class of limited memory preconditioners for the solution of sequences of linear systems. To this aim, we consider linear systems with the same symmetric positive definite matrix and multiple right-hand sides available in sequence. We first propose a general class of preconditioners, called Limited … Read more

    Numerical Experience with a Recursive Trust-Region Method for Multilevel Nonlinear Optimization

  • Serge Gratton
  • Annick Sartenaer
  • Philippe L. Toint
  • Mélodie Mouffe
  • Dimitri Tomanos
    • Categories Bound-constrained Optimization, Distributed Control, Optimization of Systems modeled by PDEs Tags , , , , ,

    We consider an implementation of the recursive multilevel trust-region algorithm proposed by Gratton, Mouffe, Toint, Weber (2008) for bound-constrained nonlinear problems, and provide numerical experience on multilevel test problems. A suitable choice of the algorithm’s parameters is identified on these problems, yielding a satisfactory compromise between reliability and efficiency. The resulting default algorithm is then … Read more

    Multi-Secant Equations, Approximate Invariant Subspaces and Multigrid Optimization

  • Serge Gratton
  • Philippe L. Toint
    • Categories Optimization of Systems modeled by PDEs, Unconstrained Optimization Tags , , ,

    New approximate secant equations are shown to result from the knowledge of (problem dependent) invariant subspace information, which in turn suggests improvements in quasi-Newton methods for unconstrained minimization. It is also shown that this type of information may often be extracted from the multigrid structure of discretized infinite dimensional problems. A new limited-memory BFGS using … Read more