The Markov chain approximation method is an effective and widely used approach for computing optimal values and controls for stochastic systems. It was extended to nonlinear (and p...
Recently, an optimization approach for fast visual tracking of articulated structures based on Stochastic Meta-Descent (SMD) [7] has been presented. SMD is a gradient descent with...
Matthieu Bray, Esther Koller-Meier, Nicol N. Schra...
Train Routing is a problem that arises in the early phase of the passenger railway planning process, usually several months before operating the trains. The main goal is to assign...
Alberto Caprara, Laura Galli, Leo G. Kroon, G&aacu...
We develop a variant of the Nelder-Mead (NM) simplex search procedure for stochastic simulation optimization that is designed to avoid many of the weaknesses encumbering such dire...
This paper explores an approach to global, stochastic, simulation optimization which combines stochastic approximation (SA) with simulated annealing (SAN). SA directs a search of ...