Nonconvex Optimization Using Negative Curvature within a Modified Linesearch Articles uri icon

publication date

  • September 2008

start page

  • 706

end page

  • 722

issue

  • 3

volume

  • 189

international standard serial number (ISSN)

  • 0377-2217

electronic international standard serial number (EISSN)

  • 1872-6860

abstract

  • This paper describes a new algorithm for the solution of nonconvex unconstrained optimization problems, with the property of converging to points satisfying second-order necessary optimality conditions. The algorithm is based on a procedure which, from two descent directions, a Newton-type direction and a direction of negative curvature, selects in each iteration the linesearch model best adapted to the properties of these directions. The paper also presents results of numerical experiments that illustrate its practical efficiency.