Optimization Online


A comparison of methods for traversing non-convex regions in optimization problems

Michael Bartholomew-Biggs(matqmb***at***herts.ac.uk)
Salah Beddiaf(matqsb***at***herts.ac.uk)
Bruce Christianson(comqbc***at***herts.ac.uk)

Abstract: This paper considers again the well-known problem of dealing with non-convex regions during the minimization of a nonlinear function F(x) by Newton-like methods. The proposal made here involves a curvilinear search along an approximation to the continuous steepest descent path defined by the solution of the ODE dx/dt = -grad F(x). The algorithm we develop and describe has some features in common with trust region methods; and we present some numerical experiments in which its performance is compared with some other ODE-based and trust region methods.

Keywords: non-convexity, Newton-like methods, continuous steepest descent

Category 1: Nonlinear Optimization (Unconstrained Optimization )

Citation: Unpublished report, School of Physics Astronomy & Mathematics, University of Hertfordshire, March 2018

Download: [PDF]

Entry Submitted: 03/07/2018
Entry Accepted: 03/07/2018
Entry Last Modified: 03/07/2018

Modify/Update this entry

  Visitors Authors More about us Links
  Subscribe, Unsubscribe
Digest Archive
Search, Browse the Repository


Coordinator's Board
Classification Scheme
Give us feedback
Optimization Journals, Sites, Societies
Mathematical Optimization Society