Journées de l'optimisation 2017

HEC Montréal, 8-10 mai 2017

1er Atelier Canadien sur l'optimisation des soins de santé (CHOW)

HEC Montréal, 10-11 mai 2017


HEC Montréal, 8 — 11 mai 2017

Horaire Auteurs Mon horaire

WB7 Processus de Markov / Markov decision processes

10 mai 2017 10h30 – 12h10

Salle: St-Hubert

3 présentations

  • 10h30 - 10h55

    Renewal theory based reinforcement learning for Markov processes with controlled restarts

    • Jayakumar Subramanian, prés., McGill
    • Jhelum Chakravorty,
    • Aditya Mahajan, GERAD, McGill University

    Markov processes with controlled restarts arise in networked control systems.
    Under a threshold based strategy, such processes are regenerative. Therefore,
    the optimal performance can be written in terms of the performance
    during a regenerative cycle. We exploit this relationship to develop a
    sample-path based policy gradient algorithm.

  • 10h55 - 11h20

    ANNULE / A Markov-modulated End-to-end Delay Analysis of Large-scale RF-Mesh Networks with Time-slotted ALOHA and FHSS

    • Filippo Malandra, prés., Politecnico di Milano
    • Brunilde Sansò, Ecole Polytechnique de Montreal

    A new mathematical model and a methodology are proposed to evaluate the performance of large scale
    RF-Mesh Networks that use time-slotted ALOHA with Frequency Hopping Spread Spectrum. An
    analytic formulation for the delay, based on Markov-modulated modelling of the system, is derived. The
    formula can be extended to evaluate other important performance metrics. The proposed methodology
    is applied to a large scale network of several thousands of nodes, and numerical results are reported to
    show the wide variety of performance evaluations that are enabled. The usefulness of the assessment of
    the feasibility of different types of applications (e.g., smart-metering, sensor networks, IoT) is shown.
    An analysis of the scalability of this methodology and a comparison with simulation results are also

  • 11h20 - 11h45

    Global Inventory Planning with Loosely Coupled Markov Decision processes

    • Thierry Moisan, prés., Université Laval
    • Éric Prescott Gagnon, JDA Software
    • Yossiri Adulyasak, HEC Montréal

    We present a general approach to plan the inventory level of slow-moving items where service level targets are applied on a set of items. Loosely coupled Markov decision processes are used within a column generation algorithm with the objective of minimizing overall costs while satisfying service level targets.