This paper considers online stochastic optimization problems where uncertainties are characterized by a distribution that can be sampled and where time constraints severely limit t...
Abstract--The paper proposes a model which allows integration of services published by independent providers into scientific or business workflows. Optimization algorithms are prop...
We propose a new top down search-based algorithm for compiling AND/OR Multi-Valued Decision Diagrams (AOMDDs), as representations of the optimal set of solutions for constraint opt...
Robert Mateescu, Radu Marinescu 0002, Rina Dechter
We propose a new algorithm for solving Distributed Constraint Optimization Problems (DCOPs). Our algorithm, called DyBop, is based on branch and bound search with dynamic ordering ...
Redouane Ezzahir, Christian Bessiere, Imade Benela...