Fixed point quasiconvex subgradient method

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Convergence of the Proximal Point Method for Quasiconvex Minimization

This paper extends the full convergence of the classic proximal point method to solve continuous quasiconvex minimization problems in Euclidian spaces. Under the assumption that the global minimizer set is nonempty we prove the full convergence of the sequence generated by the method to a certain generalized critical point of the problem.

متن کامل

A scalarization proximal point method for quasiconvex multiobjective minimization

In this paper we propose a scalarization proximal point method to solve multiobjective unconstrained minimization problems with locally Lipschitz and quasiconvex vector functions. We prove, under natural assumptions, that the sequence generated by the method is well defined and converges globally to a Pareto-Clarke critical point. Our method may be seen as an extension, for the non convex case,...

متن کامل

Fixed Point Iteration Method

We discuss the problem of finding approximate solutions of the equation 0 ) (  x f (1) In some cases it is possible to find the exact roots of the equation (1) for example when ) (x f is a quadratic on cubic polynomial otherwise, in general, is interested in finding approximate solutions using some numerical methods. Here, we will discuss a method called fixed point iteration method and a part...

متن کامل

An Extension of the Proximal Point Method for Quasiconvex Minimization

In this paper we propose an extension of the proximal point method to solve minimization problems with quasiconvex objective functions on the Euclidean space and the nonnegative orthant. For the unconstrained minimization problem, assumming that the function is bounded from below and lower semicontinuous we prove that iterations {x} given by 0 ∈ ∂̂(f(.)+(λk/2)||.−x||)(x) are well defined and if,...

متن کامل

An infeasible-point subgradient method using adaptive approximate projections

We propose a new subgradient method for the minimization of nonsmooth convex functions over a convex set. To speed up computations we use adaptive approximate projections only requiring to move within a certain distance of the exact projections (which decreases in the course of the algorithm). In particular, the iterates in our method can be infeasible throughout the whole procedure. Neverthele...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: European Journal of Operational Research

سال: 2020

ISSN: 0377-2217

DOI: 10.1016/j.ejor.2019.09.037