Abstract

For the minimization of nonsmooth quasidifferentiable functions methods have been defined which make use of a particular structure of the function itself. This usually takes to the knowledge that the quasidifferential is a convex hull of a finite set of gradients and then stopping optimality conditions are sure to be working. In this paper a method for minimizing a general quasidifferentiable function is presented which do not assume that the objective function has any particular structure apart to be quasidifferentiable. A finite set of computed directional derivatives are used to get an approximation of the quasidifferential. The test of optimality condition and the search for a direction of descent are implemented as the solution of convenient subproblems.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.