We consider quantile optimization of black-box functions that are estimated with noise. We
propose two new iterative three-timescale local search algorithms. The first algorithm uses …

Statistics have been widely used in many disciplines including science, social science,
business, engineering, and many others. One of the most important areas in statistics is to …

We present a gradient-based algorithm for solving a class of simulation optimization
problems in which the objective function is the quantile of a simulation output random …

There are many significant applied contexts that require the solution of discontinuous
optimization problems in finite dimensions. Yet these problems are very difficult, both …

The paper is devoted to the stochastic optimistic bilevel optimization problem with quantile
criterion in the upper level problem. If the probability distribution is finite, the problem can be …

A stochastic problem of facility location formulated as a discrete bilevel problem of stochastic
programming with quantile criterion was proposed. Consideration was given there to a pair …

In this paper, we provide an approximation method for probability function and its
derivatives, which allows using the first order numerical algorithms in stochastic optimization …

We propose a setting for a bilevel stochastic linear programming problem with quantile
criterion. We study continuity properties of the criterial function and prove the existence …

Consideration was given to the two-step problem of stochastic optimization with a bilinear
model which describes the problem of forming the securities portfolio consisting of some risk …

We consider two-stage stochastic programming models with quantile criterion as well as
models with a probabilistic constraint on the random values of the objective function of the …