On the convergence properties of the projected gradient method for convex optimization

On the convergence properties of the projected gradient method for convex optimization

When applied to an unconstrained minimization problem with a convex objective, the steepest descent method has stronger convergence properties than in the noncovex case: the whole sequence converges to an optimal solution under the only hypothesis of existence of minimizers (i.e. without assuming e.g. boundedness of the level sets). In this paper we look at the projected gradient method for con...

“the effect of risk aversion on the demand for life insurance: the case of iranian life insurance market”

abstract: about 60% of total premium of insurance industry is pertained?to life policies in the world; while the life insurance total premium in iran is less than 6% of total premium in insurance industry in 2008 (sigma, no 3/2009). among the reasons that discourage the life insurance industry is the problem of adverse selection. adverse selection theory describes a situation where the inf...

Strong Convergence of a Projected Gradient Method

Inexact projected gradient method for vector optimization

In this work, we propose an inexact projected gradient-like method for solving smooth constrained vector optimization problems. In the unconstrained case, we retrieve the steepest descent method introduced by Graña Drummond and Svaiter. In the constrained setting, the method we present extends the exact one proposed by Graña Drummond and Iusem, since it admits relative errors on the search dire...

Spectral projected gradient method for stochastic optimization

We consider the Spectral Projected Gradient method for solving constrained optimization porblems with the objective function in the form of mathematical expectation. It is assumed that the feasible set is convex, closed and easy to project on. The objective function is approximated by a sequence of Sample Average Approximation functions with different sample sizes. The sample size update is bas...