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

WB2 Transport collaboratif / Collaborative transportation

10 mai 2017 10h30 – 12h10

Salle: Gérard-Parizeau

Présidée par Leandro Coelho

4 présentations

  • 10h30 - 10h55

    Enhancing air traffic management through collaboration

    • Soumia Ichoua, prés., Embry-Riddle Aeronautical University

    Under the concept of Collaborative Air Traffic Management, traffic managers and flight operators/planners share data and collaborate to enhance the NAS overall operational efficiency. We propose an optimization procedure that seeks to achieve a good trade-off between overall system efficiency, optimal individual stakeholders’ goals and a good level of equity.

  • 10h55 - 11h20

    Combinatorial bid generation for transportation procurement auctions taking into account carrier’s risk behaviour

    • waddhah mhamdi, prés., génie industriel

    for a carrier, the construction of a bid to submit into a transportation procurement combinatorial auction can be of a great difficulty. This latter is even more critical when the carrier should take into account the previous engagements he's enrolled with.
    in this project, we developped an advisor that helps the carrier to generate two OR bids B1 and B2 (different one from another) in a way to maximize his expected profits if he is to face the cases : win B1, win B2 or win both

  • 11h20 - 11h45

    A Large neighbourhood search heuristic for bid construction problem in total truckload transportation procurement auctions

    • Farouk Hammami, prés., CIRRELT
    • Monia Rekik, Université Laval
    • Leandro C. Coelho, Université Laval

    This work deals with the Bid Construction Problem in total Truckload Combinatorial Auctions. We formulate it as a mathematical model maximizing the profit. Results are compared to those obtained for a developed LNS heuristic and tested on randomly generated instances. Computational results show that the LNS heuristic performs well in terms of CPU time and solution quality.

  • 11h45 - 12h10

    Cooperation between shippers to reduce LTL shipping cost and GHG emissions

    • Jacques Renaud, Université Laval, CIRRELT
    • Leandro C. Coelho, prés., Université Laval
    • Ariane Legault-Michaud, ULaval
    • Florence Bouchard, ULaval
    • Thomas Chabot, Univesité Laval

    In this article we present how collaboration between local enterprises can be managed to reduces LTL shipping costs and GHG emissions. Based on the data of here local enterprises we developed models to optimize either the shipping cost or the GHG emissions. By large simulation experiments we show under which conditions such a collaboration can be profitable.