In this article, we describe an approximate dynamic programming (ADP) approach to compute lower bounds on the optimal value function for a discrete time, continuous space, and infinite horizon setting. The iteratively constructs family of bounding functions by using so-called Bellman inequality. novelty our is that, at each iteration, aim that maximizes point-wise maximum taken with computed th...

Abstract We study the problem of scheduling container transport in synchromodal networks considering stochastic demand. In networks, transportation modes can be selected dynamically given actual circumstances and performance is measured over entire network time. model this as a Markov Decision Process propose heuristic solution based on Approximate Dynamic Programming (ADP). Due to multi-period...

For years, there has been interest in approximation methods for solving dynamic programming problems, because of the inherent complexity computing optimal solutions characterized by Bellman's principle optimality. A wide range approximate (ADP) now exists. It is great to guarantee that performance an ADP scheme be at least some known fraction, say ?, optimal. This letter introduces a general ap...