Journées de l'optimisation 2016

HEC Montréal, Québec, Canada, 2 — 4 mai 2016

Horaire Auteurs Mon horaire
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MB7 Transport / Transportation II

2 mai 2016 15h30 – 17h10

Salle: TAL Gestion globale d'actifs inc.

Présidée par Philippe Lebeau

3 présentations

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    15h30 - 15h55

    A bike route choice model using recursive logit

    • Maëlle Zimmermann, prés., Université de Montréal
    • Emma Frejinger, DIRO and CIRRELT
    • Tien Mai, Université de Montréal

    We estimate a bike route choice model based on GPS observations in a real network using recursive logit. Our contributions are: i) numerical estimation results revealing cyclists’ preferences, ii) simulation of bike traffic on network’s links and comparison with observed counts, iii) development of bike accessibility measure from the model.

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    15h55 - 16h20

    Diesel or/and battery electric vehicles: Which mixed technology fleet for city logistics?

    • Philippe Lebeau, prés., Vrije Universiteit Brussel
    • Cathy Macharis, Vrije Universiteit Brussel, MOSI-Transport&Logistics
    • Joeri Van Mierlo, Vrije Universiteit Brussel
    • Cedric De Cauwer, Vrije Universiteit Brussel
    • Wouter Verbeke, Vrije Universiteit Brussel
    • Thierry Coosemans, Vrije Universiteit Brussel

    Operational constraints are often mentioned as the most critical barrier to the adoption of battery electric vehicles (BEVs) in city logistics. By means of a fleet size and mix vehicle routing problem with time windows adapted to BEVs, we investigate the type of environment where BEVs are the most suited.

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    16h20 - 16h45

    On the value iteration method for recursive route choice models

    • Mai Anh Tien, prés., Université de Montréal
    • Emma Frejinger, DIRO and CIRRELT

    This talk concerns the use of the value iteration method for estimating recursive route choice models, which are dynamic discrete choice models without discount factor. We establish conditions for the existence of a fixed point solution, and for the convergence of the value iteration method. We also derive the Newton-Kantorovich iterations and develop a switching strategy that allows to quickly solve the value functions for real networks.