Dânâ Davar

A Finite-Difference Trust-Region Method for Convexly Constrained Smooth Optimization

  • Dânâ Davar
  • Geovani Nunes Grapiglia
    • Categories Bound-constrained Optimization, Nonlinear Optimization Tags , , , ,

    We propose a derivative-free trust-region method based on finite-difference gradient approximations for smooth optimization problems with convex constraints. The proposed method does not require computing an approximate stationarity measure. For nonconvex problems, we establish a worst-case complexity bound of \(\mathcal{O}\!\left(n\left(\frac{L}{\sigma}\epsilon\right)^{-2}\right)\) function evaluations for the method to reach an \(\left(\frac{L}{\sigma}\epsilon\right)\)-approximate stationary point, where \(n\) is the … Read more

    TRFD: A Derivative-Free Trust-Region Method Based on Finite Differences for Composite Nonsmooth Optimization

  • Dânâ Davar
  • Geovani Nunes Grapiglia
    • Categories Nonsmooth Optimization Tags , , ,

    In this work we present TRFD, a derivative-free trust-region method based on finite differences for minimizing composite functions of the form \(f(x)=h(F(x))\), where \(F\) is a black-box function assumed to have a Lipschitz continuous Jacobian, and \(h\) is a known convex Lipschitz function, possibly nonsmooth. The method approximates the Jacobian of \(F\) via forward finite … Read more