Crowd behaviour modelling developments through mixed integer programming : the case of airport queue management

Doostmohammadi, Mahdi and Fragniere, Emmanuel and Holdsworth, Rosanna; (2020) Crowd behaviour modelling developments through mixed integer programming : the case of airport queue management. In: ICITM 2020 - 2020 9th International Conference on Industrial Technology and Management. Institute of Electrical and Electronics Engineers Inc., GBR, pp. 32-36. ISBN 9781728143064 (https://doi.org/10.1109/ICITM48982.2020.9080350)

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Abstract

Crowd behaviour is difficult to predict and might not be easy to translate. A number of mathematical and psychological models are proposed in the literature to investigate crowd behaviour. In this paper, we exploit mixed integer programming to model crowd behaviour with multiple time periods. This research improves upon methods by Breer et al. (2015) for determining the number of active agents and solving the problem of reducing this number by controlling reputations in a single period, under the added assumption of a reputation model of interactions (Granovetter, 1978). Thus, this paper goes on to extend the single period reputation control problem and solution to the case of multiple time periods. This class of problems requires a mixed integer program to be solved several times with a varying constraint and a varying number of variables. This model is then supported by a promising case study of queue management at airport security gates.

ORCID iDs

Doostmohammadi, Mahdi ORCID logoORCID: https://orcid.org/0000-0002-6865-8058, Fragniere, Emmanuel and Holdsworth, Rosanna;
  • Item type:Book Section
    ID code:73037
    Dates:
    Date
    Event
    30 April 2020
    Published
    11 February 2020
    Accepted
    Notes:© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
    Subjects:Social Sciences > Industries. Land use. Labor > Management. Industrial Management
    Department:Strathclyde Business School > Management Science
    Depositing user: Pure Administrator
    Date deposited:06 Jul 2020 10:20
    Last modified:11 Nov 2024 15:21
    Related URLs:
    URI:https://strathprints.strath.ac.uk/id/eprint/73037
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