We study the generalized assignment problem, under a probabilistic model for its cost and requirement parameters. First we address the issue of feasibility by deriving a tight condition on the probabilistic model that ensures that the corresponding problem instances are feasible with the...

In this note we address the problem of constructing dominating sets for problems whose objective is a componentwise nondecreasing function of (possibly an infinite number of) convex functions, and we show how to obtain a convex dominating set in terms of dominating sets of simpler problems.

In this paper we consider properties of the central path and the analytic center of the optimal face in the context of parametric linear programming. We first show that if the right-hand side vector of a standard linear program is perturbed, then the analytic center of the optimal face is...

In this paper we analyze the sensitivity of unit root inference to nonlinear transformations through Bayesian techniques. We make joint inference about the Box-Cox transformation, which includes the cases yt and log(yt), and the unit root. When we apply our method to the fourteen Nelson-Plosser...