A Mathematical Model for In-Person Office Assignment During COVID-19


  • Daryl Santos Binghamton University




COVID-19; workforce planning; mathematical modeling


The global pandemic that is COVID-19 has altered our world as we know it. Educational systems have been seriously affected, businesses – whether “essential” or not – have been severely stressed, how people socialize has, perhaps forever, been changed, and telecommuting is the new norm. The purpose of this paper is to discuss a situation wherein a company was having difficulty in scheduling their in-person office staffing in a move to allow rotational schedules for their employees to decongest their office when an entirely telecommuting operation was not possible. Due to the different types of employees, their various work-related constraints, and the need to minimize the number of bodies in the office while addressing minimum coverage necessary to perform the company’s daily activities, a quick solution to their scheduling/assignment needs was not obvious or trivially obtained. As such, mathematical models, specifically, integer programming assignment models, were developed and ultimately solved using the Python/Gurobi solver to address their scheduling needs. This paper will describe the constraints faced by the company and the models developed to solve their tricky assignment problem.


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How to Cite

Santos, D. (2021). A Mathematical Model for In-Person Office Assignment During COVID-19. Industrial and Systems Engineering Review, 9(1), 68-74. https://doi.org/10.37266/ISER.2021v9i1.pp68-74