4 présentations

• 
  15h30 - 15h55

  Using GPS information to improve transportation planning in the furniture industry and reduce GHG emissions

  • Leandro C. Coelho, Université Laval
  • Jacques Renaud, Université Laval, CIRRELT
  • Khaled Belhassine, Université Laval
  • Rabie Jaballah, Université Laval

  In this presentation we show how we acquire, transform and analyze GSP data from our partner to determine the congestion faced by its vehicle fleet. We develop time dependent algorithms to optimize their routes in function of congestion data. We can determine the best departure time to minimize the transportation time and evaluate the annual savings in terms of cost and GHG emissions.

• 
  15h55 - 16h20

  Production routing problem with emission minimization

  • Maryam Darvish, prés., Université Laval
  • Claudia Archetti, University of Brescia
  • Leandro C. Coelho, Université Laval

  Aiming to compare the effect of operational decisions on costs and emissions, we reassess the production routing problem under new objectives. We study an integrated system of production, inventory, and routing decisions, in which the commodity produced at the plant is shipped to the customers over a finite time horizon.

• 
  16h20 - 16h45

  A MIP Formulation For The Rapid Transit Line Design Problem

  • Souhaila Elfilali, prés., Université de Montréal
  • Bernard Gendron, Université de Montréal, CIRRELT
  • Gilbert Laporte, HEC Montréal

  We propose a tight formulation of the rapid transit line location problem, which consists of positioning stations and segments between them to form a line, in the objective of maximizing O-D pairs coverage under topologic and budget constraints. We test our formulation on artificial and real-life instances.

• 
  16h45 - 17h10

  The limited stop bus service design problem with stochastic passenger assignment

  • Homero Larrain, prés., PUC
  • Juan Carlos Muñoz, Pontificia Universidad Católica de Chile
  • Guillermo Soto, Pontificia Universidad Católica de Chile

  The solution of this non-linear problem must account for bus capacity and reflect user behavior. Using a bi-level approach, we improve the solution time of a previous algorithm and allow for stochastic assignment, which is arguably more realistic and robust than the commonly used deterministic assignment.