TY - GEN
T1 - Crowd Behaviour Modelling Developments through Mixed Integer Programming
T2 - 9th International Conference on Industrial Technology and Management, ICITM 2020
AU - Doostmohammadi, Mahdi
AU - Fragniere, Emmanuel
AU - Holdsworth, Rosanna
PY - 2020/2
Y1 - 2020/2
N2 - 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.
AB - 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.
KW - crowd behavior
KW - decision aid tool
KW - mixed integer programming
KW - reputation control model
KW - threshold model
UR - http://www.scopus.com/inward/record.url?scp=85084951740&partnerID=8YFLogxK
U2 - 10.1109/ICITM48982.2020.9080350
DO - 10.1109/ICITM48982.2020.9080350
M3 - Chapter in a published conference proceeding
AN - SCOPUS:85084951740
T3 - ICITM 2020 - 2020 9th International Conference on Industrial Technology and Management
SP - 32
EP - 36
BT - ICITM 2020 - 2020 9th International Conference on Industrial Technology and Management
PB - IEEE
Y2 - 11 February 2020 through 13 February 2020
ER -