• Publications
  • Influence
Dynamic programming and Markov potential theory
  • 220
  • 22
Multimodularity, Convexity, and Optimization Properties
TLDR
In this paper we investigate the properties of multimodular functions. Expand
  • 102
  • 16
Balanced sequences and optimal routing
The objective pursued in this paper is two-fold. The first part addresses the following combinatorial problem: is it possible to construct an infinite sequence over n letters where each letter isExpand
  • 99
  • 11
  • PDF
Discrete-Event Control of Stochastic Networks - Multimodularity and Regularity
TLDR
Preface.- Part I: Theoretical Foundations: Multimodularity, Convexity and Optimization Balanced Sequences Stochastic Event Graphs Applications in Queuing Networks Optimal Routing in two Deterministic Queues. Expand
  • 85
  • 9
Contraction Conditions for Average and α-Discount Optimality in Countable State Markov Games with Unbounded Rewards
TLDR
The goal of this paper is to provide a theory of N-person Markov games with unbounded cost, for a countable state space and compact action spaces. Expand
  • 68
  • 9
Constrained admission control to a queueing system
We consider an exponential queue with arrival and service rates depending on the number of jobs present in the queue. The queueing system is controlled by restricting arrivals. Typically, a goodExpand
  • 89
  • 7
Constrained Undiscounted Stochastic Dynamic Programming
TLDR
We investigate the computation of optimal policies in constrained discrete stochastic dynamic programming with the average reward as utility function. Expand
  • 109
  • 7
Blackwell optimality in the class of all policies in Markov decision chains with a Borel state space and unbounded rewards
TLDR
This paper is the second part of our study of Blackwell optimal policies in Markov decision chains with a Borel state space and unbounded rewards. Expand
  • 37
  • 7
Average, Sensitive and Blackwell Optimal Policies in Denumerable Markov Decision Chains with Unbounded Rewards
In this paper we consider a discrete-time Markov decision chain with a denumerable state space and compact action sets and we assume that for all states the rewards and transition probabilitiesExpand
  • 59
  • 6
STOCHASTIC INEQUALITIES FOR AN OVERFLOW MODEL
A general method to obtain insensitive upper and lower bounds for the stationary distribution of queueing networks is sketched. It is applied to an overflow model. The bounds are shown to be validExpand
  • 31
  • 6
...
1
2
3
4
5
...