This paper studies the use of decomposition techniques to quickly find high-quality solutions to large-scale vehicle routing problems with time windows. It considers an adaptive d...
Sparse Grids are the basis for efficient high dimensional approximation and have recently been applied successfully to predictive modelling. They are spanned by a collection of si...
The queueing Petri net (QPN) paradigm provides a number of benefits over conventional modeling paradigms such as queueing networks and generalized stochastic Petri nets. Using qu...
Contact interval between moving vehicles is one of the key metrics in vehicular ad hoc networks (VANETs), which is important to routing schemes and network capacity. In this work,...
Yong Li, Depeng Jin, Pan Hui, Li Su, Lieguang Zeng
Large scale learning is often realistic only in a semi-supervised setting where a small set of labeled examples is available together with a large collection of unlabeled data. In...