4 présentations

• 
  15h30 - 15h55

  Stochastic single-allocation hub location

  • Borzou Rostami, prés., Polytechnique Montreal
  • Nicolas Kammerling, TU Dortmund University
  • Christoph Buchheim, TU Dortmund University
  • Joe Naoum-Sawaya, Ivey Business School, Western University
  • Uwe Clausen, TU Dortmund University

  This paper presents a variation of the single allocation hub location problem under demand uncertainty. Namely, we consider variable allocations, meaning that the allocation of the spokes to the hubs can be altered after the uncertainty is realized. We model the problem as a two-stage stochastic program and reformulate it as a convex mixed-integer nonlinear program. We develop a customized solution approach based on cutting planes where the cut-generating subproblems are solved combinatorially, i.e. without an optimization solver. Extensive computational results show that the proposed cutting plane approach outperforms the direct solution of the problem using the state-of-the-art solver GUROBI as well the L-shaped decomposition, which is a common approach for addressing two-stage stochastic programs with recourse.
• 
  15h55 - 16h20

  A branch-and-cut based heuristic for the bid construction problem with stochastic profits

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

  In combinatorial auctions for the procurement of transportation services, bid construction problems (BCPs) have been studied since the 1990s. A BCP must be solved by each carrier participating in the transportation procurement auction in order to determine the set of contracts that are the most profitable to bid on and the associate bid price. These decisions are generally made under uncertainty due to other competing carriers’ offers. In this work, we conisder a BCP with stochastic prices through different scenarios and propose a hybrid heuristic to generate bids and associated prices while considering risks associated to bids’ loss. These risks are handled as new constraints dynamically added via a branch-and-cut algorithm.
• 
  16h20 - 16h45

  Stochastic integrated workforce training and operations planning for maintenance service providers

  • Shayan Tavakoli Kafiabad, prés., Concordia University
  • Masoumeh Kazemi Zanjani, Concordia University
  • Mustapha Nourelfath, Université Laval

  In this project, an integrated multi-period mathematical model is proposed to obtain the optimal procurement, production, inventory, and training plan with the goal of minimizing the total operations cost of maintenance service providers. Then, a multi-stage stochastic programming with recourse is proposed to deal with repair time uncertainty.

  Keywords: Workforce training, Operations planning, Multi-stage stochastic programming
• 
  16h45 - 17h10

  A two-stage robust model for perishable inventory management problems

  • Pedram Hooshangitabrizi, prés., Ph.D. Candidate
  • Ivan Contreras, Concordia University and Interuniversity Research Centre on Enterprise Networks, Logistics and Transportation (CIRRELT), Montreal, Canada
  • Nadia Bhuiyan, Concordia University, Montreal, Canada
  • Hossein Hashemi Doulabi, Concordia University and Interuniversity Research Centre on Enterprise Networks, Logistics and Transportation (CIRRELT), Montreal, Canada

  Managing inventories of perishable items is a highly challenging task, mainly due to demand uncertainty, limited shelf life, and the multi-period nature of inventory control problems. In this work, we propose a two-stage robust optimization model that focuses on minimizing operational costs, as well as shortage and wastage. To solve the two-stage robust model, an effective and efficient column-and-constraint generation algorithm is proposed. Several computational experiments are conducted to show the performance of the developed algorithm.