In this paper we study a challenging call center operation problem. The goal of our analysis is to identify an optimal policy for allocating tasks to agents. As a first step, we discuss promising randomized policies and use stochastic approximation for finding the optimal randomized policy when...

We study a stochastic dynamic game of process innovation in which firms can initiate and terminate R&D efforts and production at different times. We discern the impact of knowledge spillovers on the investments in existing markets, as well as on the likely structure of newly forming markets, for...

This paper considers a general class of stochastic dynamic choice models with discrete and continuous decision variables. This class contains a variety of models that are useful for modeling intertemporal household decisions under risk. Our examples are drawn from the field of development...

The Cross Entropy method is a well-known adaptive importance sampling method for rare-event probability estimation, which requires estimating an optimal importance sampling density within a parametric class. In this article we estimate an optimal importance sampling density within a wider...

In this paper we describe a Sequential Importance Sampling (SIS) procedure for counting the number of vertex covers in general graphs. The performance of SIS depends heavily on how close the SIS proposal distribution is to a uniform one over a suitably restricted set. The proposed algorithm...

In linear-quadratic control (LQC) problems with singular control cost matrix and/or singular transition matrix, we derive a reduction of the dimension of the Riccati matrix, simplifying iteration and solution. Employing a novel transformation, we show that, under a certain rank condition, the...

In this paper, we apply a dynamic innovation diffusion framework to model adoption of full electric vehicles where we explicitly distinguish three major phases of adoption: introduction, growth and maturity. We combine this approach with an SP study to elicit individual preferences for...

This discussion paper resulted in a publication in <Stochastic Models</I> (2012). Volume 28(3), pages 478-502.<P> We apply the splitting method to three well-known counting problems, namely 3-SAT, random graphs with prescribed degrees, and binary contingency tables. We present an enhanced version of the splitting method...</p></stochastic>

We compare three stochastic user equilibrium traffic assignment models multinomial probit, nested logit, and generalized nested logit), using a congestible transport network. We test the models in two situations: one in which they have theoretically equivalent coefficients, and one in which they...

Kernel ridge regression is gaining popularity as a data-rich nonlinear forecasting tool, which is applicable in many different contexts. This paper investigates the influence of the choice of kernel and the setting of tuning parameters on forecast accuracy. We review several popular kernels,...