Bayesian learning, widely used in many applied data-modeling problems, is often accomplished with approximation schemes because it requires intractable computation of the posterio...
We study a model that incorporates a budget constraint in a decision making problem. Our goal is to maximize the expected wealth, where in each time period we can either stop the ...
We give a short proof of a result of Tovey [6] on the inapproximability of a scheduling problem known as precedence constrained class sequencing. In addition, we present an approxi...
abstract NP-hard optimization problem, in a general sense. From the observation that, intuitively, there are many connections among categorical concepts and structural complexity n...
Liara Aparecida dos Santos Leal, Dalcidio Moraes C...
Combinatorial allocation problems require allocating items to players in a way that maximizes the total utility. Two such problems received attention recently, and were addressed ...