Queuing Safely for Elevator Systems Amidst a Pandemic

Ananthanarayanan, S. M., Branas, C. C., Elmachtoub, A. N., Stein, C. S., & Zhou, Y. (2022). Queuing safely for elevator systems amidst a pandemic. Production and Operations Management, 00 1– 18. https://doi.org/10.1111/poms.13686

29 Pages Posted: 28 Dec 2020 Last revised: 19 Apr 2022

See all articles by Sai Mali Ananthanarayanan

Sai Mali Ananthanarayanan

Columbia University - Department of Industrial Engineering and Operations Research & Data Science Institute

Charles C. Branas

Columbia University - Department of Epidemiology

Adam N. Elmachtoub

Department of Industrial Engineering and Operations Research & Data Science Institute, Columbia University

Clifford Stein

Columbia University - Department of Industrial Engineering and Operations Research & Data Science Institute

Yeqing Zhou

Eindhoven University of Technology (TUE) - Department of Industrial Engineering and Innovation Sciences

Date Written: December 21, 2020

Abstract

The requirement of social distancing during the COVID-19 pandemic has presented significant challenges for high-rise buildings, which heavily rely on elevators for vertical transportation. In particular, the need for social distancing has reduced elevator capacity typically by at least two-thirds or as much as over 90% the normal amount. This reduction is a serious concern, as reduced elevator capacities cause large queues to build up in lobbies, which makes social distancing difficult and results in large wait times. The objective of this study is to safely manage the elevator queues by proposing simple, technology-free interventions that drastically reduce the waiting time and length of lobby queues. We use mathematical modeling, epidemiological expertise, and simulation to design and evaluate our interventions. The key idea is to explicitly or implicitly group passengers that are going to the same floor into the same elevator as much as possible. In the Cohorting intervention, we attempt to find passengers going to the same floor as the first person in the queue. In the Queue Splitting intervention, we create a different queue for different groups of floors. Based on simulation and analytical findings, Cohorting and Queue Splitting can significantly reduce queue length and wait time, while also maintaining safety from viral transmission in otherwise crowded elevators, building lobbies, and entrances. These interventions are generally accessible for many buildings since they do not require programming the elevators, and rely on only using signage and/or a queue manager to guide passengers.

Keywords: elevator systems, COVID-19, queues, vertical transportation, simulation, transportation engineering, pandemic

Suggested Citation

Ananthanarayanan, Sai Mali and Branas, Charles C. and Elmachtoub, Adam and Stein, Clifford and Zhou, Yeqing, Queuing Safely for Elevator Systems Amidst a Pandemic (December 21, 2020). Ananthanarayanan, S. M., Branas, C. C., Elmachtoub, A. N., Stein, C. S., & Zhou, Y. (2022). Queuing safely for elevator systems amidst a pandemic. Production and Operations Management, 00 1– 18. https://doi.org/10.1111/poms.13686, Available at SSRN: https://ssrn.com/abstract=3755062 or http://dx.doi.org/10.2139/ssrn.3755062

Sai Mali Ananthanarayanan (Contact Author)

Columbia University - Department of Industrial Engineering and Operations Research & Data Science Institute ( email )

500 West 120th Street
New York, NY 10027

Charles C. Branas

Columbia University - Department of Epidemiology ( email )

722 West 168th Street
New York, NY 10032
United States

Adam Elmachtoub

Department of Industrial Engineering and Operations Research & Data Science Institute, Columbia University ( email )

535F S.W. Mudd Building
500 West 120th Street
New York, NY 10027
United States

HOME PAGE: http://www.columbia.edu/~ae2516/

Clifford Stein

Columbia University - Department of Industrial Engineering and Operations Research & Data Science Institute ( email )

500 West 120th Street
New York, NY 10027

Yeqing Zhou

Eindhoven University of Technology (TUE) - Department of Industrial Engineering and Innovation Sciences ( email )

Eindhoven
Netherlands

HOME PAGE: http://research.tue.nl/en/persons/yeqing-zhou

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