Stochastic optimization problems provide a means to model uncertainty in the input data where the uncertainty is modeled by a probability distribution over the possible realizatio...
The application of genetic algorithms (GAs) to many optimization problems in organizations often results in good performance and high quality solutions. For successful and efficien...
Maroun Bercachi, Philippe Collard, Manuel Clergue,...
Chordal graphs can be used to encode dependency models that are representable by both directed acyclic and undirected graphs. This paper discusses a very simple and efficient algo...
We present an optimization algorithm that combines active learning and locally-weighted regression to find extreme points of noisy and complex functions. We apply our algorithm to...
This article presents a detailed discussion of LRE-TL (Local Remaining Execution - TL-plane), an algorithm that schedules hard real-time periodic and sporadic task sets with uncon...