Markov decision processes (MDPs) and contingency planning (CP) are two widely used approaches to planning under uncertainty. MDPs are attractive because the model is extremely gen...
In this paper, we present a stochastic model for the dynamic fleet management problem with random travel times. Our approach decomposes the problem into time-staged subproblems by...
A compiler optimization is sound if the optimized program that it produces is semantically equivalent to the input program. The proofs of semantic equivalence are usually tedious....
We present a brokering service for the adaptive management of composite services. The goal of this broker is to dynamically adapt at runtime the composite service configuration, ...
This paper addresses the need for nonlinear programming algorithms that provide fast local convergence guarantees no matter if a problem is feasible or infeasible. We present an a...