20 citations · 31 across the 4 of their papers we have counts for
4 papers
Deep reinforcement learning for the dynamic vehicle dispatching problem: An event-based approach
Edyvalberty Alenquer Cordeiro, Anselmo Ramalho Pitombeira-Neto
The dynamic vehicle dispatching problem corresponds to deciding which vehicles to assign to requests that arise stochastically over time and space. It emerges in diverse areas, suc…
A Reinforcement Learning Approach to the Stochastic Cutting Stock Problem
Anselmo R. Pitombeira-Neto, Arthur H. Fonseca Murta
We propose a formulation of the stochastic cutting stock problem as a discounted infinite-horizon Markov decision process. At each decision epoch, given current inventory of items,…
Heterogeneous Prestressed Precast Beams Multiperiod Production Planning Problem: Modeling and Solution Methods
Kennedy Araujo, Tiberius Bonates, Bruno Prata +1
A prestressed precast beam is a type of beam that is stretched with traction elements. A common task in a factory of prestressed precast beams involves fulfilling, within a time ho…
Bayesian inference on dynamic linear models of day-to-day origin-destination flows in transportation networks
Anselmo Ramalho Pitombeira-Neto, Carlos Felipe Grangeiro Loureiro, Luis Eduardo Carvalho
Estimation of origin-destination (OD) demand plays a key role in successful transportation studies. In this paper, we consider the estimation of time-varying day-to-day OD flows gi…