Minimizing a stochastic convex function subject to stochastic constraints and some applications
Probability
2020-02-27 v2 Optimization and Control
Abstract
In the simplest case, we obtain a general solution to a problem of minimizing an integral of a nondecreasing right continuous stochastic process from zero to some nonnegative random variable tau, under the constraints that for some nonnegative random variable T, tau is between zero and T a.s. and the expected value of tau is some alpha. The nondecreasing process and T are allowed to be dependent. In fact a more general setup involving sigma-finite measures, rather than just probability measures is considered and some consequences for families of stochastic processes are given as special cases. Various applications are provided.
Cite
@article{arxiv.1906.09604,
title = {Minimizing a stochastic convex function subject to stochastic constraints and some applications},
author = {Royi Jacobovic and Offer Kella},
journal= {arXiv preprint arXiv:1906.09604},
year = {2020}
}
Comments
22 pages