SCRO / Journées de l'optimisation

HEC Montréal, 29-31 mai 2023


HEC Montréal, 29 — 31 mai 2023

Horaire Auteurs Mon horaire

SCLII Supply Chains and Logistics II

29 mai 2023 15h30 – 17h10

Salle: BMO - CSC (vert)

Présidée par Daniel Ocampo Giraldo

3 présentations

  • 15h30 - 15h55

    Impact of 3D printing on Spare Parts Logistics Under Dual Sourcing

    • Parang Zadtootaghaj, prés.,
    • Borzou Rostami,

    This study presents a general framework and solution methodology for industrial goods logistics subject to the availability of 3D printing technology. We consider multiple products facing stochastic demands and utilize the make-to-stock policy versus the make-to-order (3D printing) method that employs a multi-class priority queue. The objective is to minimize the long-run average system cost by assigning future demands to stock or print. This framework is then extended to address the multi-item dual sourcing problem. We develop optimization algorithms to derive optimal policies for each framework. The results of each modeling framework and the complexity of the optimization algorithms will be discussed.
    Keywords: integer programming, logistics, manufacturing

  • 15h55 - 16h20

    Minmax regret maximum covering location problem

    • Robert Benkoczi, University of Lethbridge
    • Saeid Jafaripour, prés., University of Lethbridge

    The Maximum Covering Location Problem (MCLP) is a widely studied optimization problem in facility location. The objective is to find a placement of a given number of facilities to maximize the profit obtained from customers situated within the given maximum service radius from a facility. In the robust MCLP, the customer profits are uncertain and given as an interval of possible values. Any value assignment from these intervals determines a scenario for the uncertain MCLP.

    In this abstract, we report preliminary results on solving the minmax regret version of the above uncertain MCLP. The regret of a solution to an uncertain optimization problem is defined as the difference between the cost of the solution under the worst case scenario and the optimal cost of the worst case scenario. Unlike other problems in facility location, MCLP was not sufficiently investigated under the minmax regret criterion. The contribution closest to our work concerns the set-cover version of the problem where all customers are covered. We expand this previous study by exploring several strategies to generate cuts in a Benders decomposition formulation for the minmax regret MCLP.

  • 16h20 - 16h45

    Collaborative Regional Distribution Network Design for perishable products

    • Daniel Ocampo-Giraldo, prés., ESG-UQÀM
    • Ana María Anaya Arenas, ESG - UQAM
    • Janosch Ortmann, UQAM

    The benefits of collaboration and pooling of resources have been studied in commercial logistics for over two decades. Here, companies seek to define and plan a distribution network, using common means, to improve efficiency and efficacy. Moreover, in non-commercial settings (communitarian, humanitarian, or healthcare) such strategies become more interesting, especially when facing very limited resources, strong labor shortages, and seasonal demand. Inspired by the cases of a non-commercial sector in Quebec, we present the challenges and the advantage of tackling said business models. From a Bioalimentary consortium in Québec, we present a network design model for the distribution of perishable products inside the region of Laurentides. The selection of intermediate facilities, the fleet selection, and the routes to collect and deliver items- guarantee commodities' preservation over time- will be integrated into an optimization model.