This study concerns a generic model-free stochastic optimization problem requiring the minimization of a risk function defined on a given bounded domain in ...

We consider an ATM switch model, in which each of <i>N</i> sources is a Markov modulated rate process. We look at some approximations that have been propos...

Combining parallel multiple recursive sequences provides an efficient way of implementing random number generators with long periods and good structural pro...

Central limit theorems are obtained for the PARMSR (perturbation analysis Robbins-Monro single run) algorithm with averaging, updated either after every reg...

Convergence rate results are derived for a stochastic optimization problem where a performance measure is minimized with respect to a vector parameter <img ...

Uniformity tests based on a discrete form of entropy are introduced and studied in the context of empirical testing of uniform random number generators. Nu...

We give an overview of the main techniques for generating uniform random numbers of computers. Theoretical and practical issues are discussed.

We consider a class of stochastic models for which the performance measure is defined as a mathematical expectation that depends on a parameter <img src="th...

In this work, we examine how to combine the score function method with the standard crude Monte Carlo and experimental design approaches, in order to evalua...

We analyze the random number generators obtained by combining two or more multiple recursive generators. We study the lattice structure of such combined gen...

In this paper, we develop mathematical machinery for verifying that a broad class of general state space Markov chains reacts smoothly to certain types of p...

Approaches like infinitesimal perturbation analysis and the likelihood ratio method have drawn a great deal of attention recently, as ways of estimating the...

The lattice structure of conventional linear congruential random number generators (LCGs), over integers, is well known. In this paper, we study LCGs in the...

Infinitesimal Perturbation Analysis (IPA) is perhaps the most efficient derivative estimation method for many practical discrete-event stochastic systems, w...

We show that in most interesting cases where infinitesimal perturbation analysis (IPA) applies for derivative estimation, a finite-difference scheme with co...

We analyze a class of combined random number generators proposed by L'Ecuyer (1988), which combines a set of linear congruential generators (LCGs) with dist...

We describe different derivative estimators for the case of steady-state performances measures and obtain the order of their convergence rates. These estima...

In this paper, we propose three combined Tausworthe random number generators with period length about 10¹⁸, whose <i>k</i>-distribution propertie...

In this paper, we suggest an approximation procedure for the solution of two-player zero-sum stochastic games with continuous state and action spaces simila...

The production scheduling problem considered in this paper is related to the planning of operations of a flexible manufacturing cell composed of a punch pres...