Shadow price of information in discrete time stochastic optimization

Optimization of Discrete-time, Stochastic Systems

Price of Correlations in Stochastic Optimization

When decisions are made in presence of high dimensional stochastic data, handling joint distribution of correlated random variables can present a formidable task, both in terms of sampling and estimation as well as algorithmic complexity. A common heuristic is to estimate only marginal distributions and substitute joint distribution by independent (product) distribution. In this paper, we study...

Discrete Time Stochastic Processes

4 Martingales 35 4.1 Examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36 4.2 Doob Decomposition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 4.3 Optional Sampling Theorem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 4.4 Inequalities and Convergence . . . . . . . . . . . ...

The Price of Information in Combinatorial Optimization

Consider a network design application where we wish to lay down a minimum-cost spanning tree in a given graph; however, we only have stochastic information about the edge costs. To learn the precise cost of any edge, we have to conduct a study that incurs a price. Our goal is to find a spanning tree while minimizing the disutility, which is the sum of the tree cost and the total price that we s...

Discrete Time Stochastic Networks

In this section we study the relation between throughput and queue-length distributions in discrete-time closed cyclic networks when the number of customers and the number of nodes grows unboundedly. To state our findings more precisely: For each positive integer N , consider a cyclic network with n(N) nodes and k(N) customers. We suppose that there are only finitely many types of nodes. That i...