CORS / Optimization Days 

HEC Montréal, May 29-31, 2023

CORS-JOPT2023

HEC Montreal, 29 — 31 May 2023

Schedule Authors My Schedule

HLPII Hub Location Problem II

May 31, 2023 03:40 PM – 05:20 PM

Location: Saine Marketing (green)

Chaired by Brenda Cobena

3 Presentations

  • 03:40 PM - 04:05 PM

    Profit Maximization in Hub Location Problems with Flow-Dependent Price: Formulations and Benders Decomposition

    • Dung Tran, presenter, The University of Edinburgh
    • Nader Azizi, The University of Edinburgh
    • Thomas Archibald, The University of Edinburgh

    This research addresses a capacitated single assignment hub location problem with profit optimization objective. A deterministic model is introduced, in which the price of serving demands between the origin - destination pairs depends on the accumulated flow traversed through inter-hub and distribution arcs. The deterministic formulation is extended as a two-stage stochastic program by incorporating demand uncertainty. To solve the models in a timely fashion, exact algorithms based on Benders decomposition are proposed. Computational experiments are presented and analyzed.

  • 04:05 PM - 04:30 PM

    Trade-off analysis in multimodal distribution network design

    • Marie-Sabine Saget, presenter, FSA-Laval University/CIRRELT
    • Maryam Darvish, Université Laval
    • Jacques Renaud, Université Laval, CIRRELT

    In recent years, logistic transporters and shipping carriers/liners have had to juggle objectives, such as cost, time, and emissions, in conducting their operations. To understand the trade-offs between these objectives, we present a multi-objective and multimodal transportation model, which we solve using the lexicographic approach to account for the hierarchy among the mentioned concerns. Based on the ranking defined in the literature, we focus on unidirectional flows to customers located along the Ontario-Quebec trade corridor from Western Europe.
    We also considered different optimization objectives (tri-objective, cost, duration, emissions) to make a comparative assessment of the impacts of logistics decisions. The obtained results highlight, in an international context, the importance of the costs related to road transport, while maritime transport monopolizes a significant share of CO2e emissions due to the interport distance. Thus, in a reality where transport decisions are mainly cost-oriented, it seems more practical to emphasize the role of multimodality in the land-based distribution network to alleviate the economic and environmental brunt tied to truck haulage. Finally, our findings underline the importance of the proposed model as a decision support tool given the significant financial gains if, for instance, the port of Montreal could handle vessels of larger capacity.

  • 04:30 PM - 04:55 PM

    The profit-oriented hub line location problem with elastic demand

    • Ivan Contreras, Concordia University
    • Cobena Brenda, presenter, Concordia University
    • Martinez Merino Luisa I., Universidad de Cadiz
    • Rodriguez-Chia Antonio M., Universidad de Cadiz

    This paper presents the profit-oriented hub line location problem with elastic demand (ED-HLLP). ED-HLLP seeks to maximize profit in terms of total reduction time by using the hub line and taking elastic demand into account. The principal contributions include the following: i) an extension of the hub line location problem (HLLP) that uses the gravity model to incorporate the elasticity of demand; ii) different mixed-integer nonlinear programming formulations for the ED-HLLP; iii) three main linear formulations due to the limitations that these formulations present. These linear formulations use the possible paths using the hub line as variables, and iv) an efficient procedure to obtain all candidate paths associated with each origin-destination, which is necessary to use in the preprocessing phase that calculates the candidate paths.
    Lastly, computational results are used to compare the proposed formulations and the benefits of the presented model using benchmark instances that are commonly used in hub location problems. In addition, a sensitivity analysis using actual data from Montreal, Canada, is carried out to demonstrate the added value of incorporating demand elasticity when using the proposed model for public transportation planning.

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