Robust Optimization is a rapidly developing methodology for handling optimization problems affected by non-stochastic "uncertain-butbounded" data perturbations. In this p...
A two-neural network approach to solving nonlinear optimal control problems is described in this study. This approach called the adaptive critic method consists of one neural netw...
Abstract. We revisit an application developed originally using Inductive Logic Programming (ILP) by replacing the underlying Logic Program (LP) description with Stochastic Logic Pr...
In this paper we study a Monte Carlo simulation based approach to stochastic discrete optimization problems. The basic idea of such methods is that a random sample is generated and...
Anton J. Kleywegt, Alexander Shapiro, Tito Homem-d...
This paper describes a way to manage the modeling and analysis of Scheduled Maintenance Systems (SMS) within an analytically tractable context. We chose a significant case study h...