Optimization Days 2019

HEC Montréal, May 13-15, 2019


HEC Montréal, 13 — 15 May 2019

Schedule Authors My Schedule

MD9 Applications II

May 13, 2019 03:30 PM – 05:10 PM

Location: Dutailier International

Chaired by Bernard Fortz

4 Presentations

  • 03:30 PM - 03:55 PM

    PAPmap: Partitioning-Assignment problem for distributed 3D mapping by UAV swarming

    • Leandro R. Costa, presenter, Polytechnique Montréal - GERAD
    • Daniel Aloise, Polytechnique Montréal
    • Andrea Lodi, Polytechnique Montreal
    • Luca Giovanni Gianoli, HumanITas

    The unmanned aerial vehicle (UAV) swarming will shortly play an essential part in plenty of real-life applications. We propose the NP-hard problem: Partitioning-Assignment Problem for distributed 3D mapping by UAV swarming. The goal is to minimize the makespan of a 3D reconstruction procedure while respecting spatial, communication, and reliability constraints./Branch-and-cut; 3D reconstruction; UAV swarming;

  • 03:55 PM - 04:20 PM

    Paint-waste management problem

    • Mucahit Cevik, Ryerson University
    • Juyoung Wang, presenter, University of Toronto
    • Amir Ali Parsaee, Ryerson University
    • Saman Hassanzadeh Amin, Ryerson University

    We study paint-waste network-flow multi-objective optimization problem with three objective functions:
    cost, transportation risk and inconvenience. The problem will be decomposed into four logistic steps:
    waste generation nodes, collection centers, treatment centers and disposal sites. We present our
    experimental results and analysis on an Ontario-based case study.

    Keywords: Household hazardous waste (HHW), Network flow, Integer programming

  • 04:20 PM - 04:45 PM

    Modeling employees' psychological well-being at work with artificial neural networks

    • Mark Somers, New Jersey Institute of Technology
    • Jose Casal, presenter, New Jersey Institute of Technology

    Predictive models of well-being have yielded weak results leading to calls for new methods and new approaches. With a national probability sample of working adults in the United States, ANN's yielded significantly greater predictive accuracy than did multiple linear regression for two indices of well-being, work stress and life satisfaction.

    Keywords; artificial neural networks; work stress; life satisfaction

  • 04:45 PM - 05:10 PM

    New models and preprocessing techniques for segment routing optimization

    • Bernard Fortz, presenter, Université Libre de Bruxelles

    Segment routing is a modern variant of source routing in computer networks, which is being developed within the SPRING and IPv6 working groups of the IETF. In a segment routed network, an ingress node may prepend a header to packets that contain a list of segments, which are instructions that are executed on subsequent nodes in the network. These instructions may be forwarding instructions, such as an instruction to forward a packet to a specific destination or interface. In this talk, we present models for traffic engineering in a network implementing segment routing on top of shortest paths routing protocols. We also present some pre-processing techniques that allow to decrease significantly the size of the resulting models, and present numerical experiments validating the approach on a large set of test instances.