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HEC Montréal, Canada, May 6 - 8, 2013

2013 Optimization Days

HEC Montréal, Canada, 6 — 8 May 2013

Schedule Authors My Schedule

TB3 Tournées de véhicules IV / Vehicle Routing Problem IV

May 7, 2013 03:30 PM – 05:10 PM

Location: St-Hubert

Chaired by Sylvain Perron

3 Presentations

  • 03:30 PM - 03:55 PM

    A Constraint Programming-Based Large Neighborhood Search for the Vehicle Routing Problem with Synchronization Constraints

    • Hossein Hojabri, presenter, Université de Montréal
    • Michel Gendreau, Polytechnique Montréal
    • Jean-Yves Potvin, Université de Montréal
    • Louis-Martin Rousseau, Polytechnique Montréal

    A synchronized VRP happens when vehicles of different types are required at some customer location to perform a service. A constraint programming-based adaptive large neighborhood search is proposed to solve this type of problem, where the latter explores large neighborhoods while the former evaluates every single move.

  • 03:55 PM - 04:20 PM

    Column Generation Heuristic for the Time-Dependent Vehicle Routing Problem with Time Windows

    • Vincent Huart, presenter, ISIMA
    • Sylvain Perron, GERAD, HEC Montréal
    • Christophe Duhamel, ISIMA

    We present a heuristic solution method for the Time-Dependent Vehicle Routing Problem with Time Windows (TDVRPTW). The method is based on column generation and on Variable Neighborhood Descend (VND). We validate our algorithm on Solomon instances adapted to the case of time-dependency.

  • 04:20 PM - 04:45 PM

    The Multi-zone Multi-trip Pickup and Delivery Problem with Time Windows and Synchronization

    • Phuong Nguyen Khanh, presenter, Université de Montréal
    • Teodor Gabriel Crainic, Université du Québec à Montréal
    • Michel Toulouse, Oklahoma State University

    Multi-zone Multi-trip Pickup and Delivery Problem with Time Windows and Synchronization (MZT-PDTWS) is an extension of the Multi-zone Multi-trip Vehicle Routing Problem with Time Windows by addressing the integration of outbound traffic into a single city logistic system. We propose a meta-heuristic to solve the problem.

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