This paper addresses a real-life personnel scheduling problem in the context of Covid19 pandemic, arising in a large Italian pharmaceutical distribution warehouse. In this case study, the challenge is to determine a schedule that attempts to meet the contractual working time of the employees, considering the fact that they must be divided into mutually exclusive groups to reduce the risk of contagion. To solve the problem, we propose a mixed integer linear programming formulation (MILP). The solution obtained indicates that optimal schedule attained by our model is better than the one generated by the company. In addition, we performed tests on random instances of larger size to evaluate the scalability of the formulation. In most cases, the results found using an open-source MILP solver suggest that high quality solutions can be achieved within an acceptable CPU time. We also project that our findings can be of general interest for other personnel scheduling problems, especially during emergency scenarios such as those related to Covid-19 pandemic.

Personnel scheduling during Covid-19 pandemic / Zucchi, Giorgio; Iori, Manuel; Subramanian, Anand. - In: OPTIMIZATION LETTERS. - ISSN 1862-4472. - 15:4(2021), pp. 1385-1396. [10.1007/s11590-020-01648-2]

Personnel scheduling during Covid-19 pandemic

Zucchi, Giorgio
Membro del Collaboration Group
;
Iori, Manuel
Membro del Collaboration Group
;
2021

Abstract

This paper addresses a real-life personnel scheduling problem in the context of Covid19 pandemic, arising in a large Italian pharmaceutical distribution warehouse. In this case study, the challenge is to determine a schedule that attempts to meet the contractual working time of the employees, considering the fact that they must be divided into mutually exclusive groups to reduce the risk of contagion. To solve the problem, we propose a mixed integer linear programming formulation (MILP). The solution obtained indicates that optimal schedule attained by our model is better than the one generated by the company. In addition, we performed tests on random instances of larger size to evaluate the scalability of the formulation. In most cases, the results found using an open-source MILP solver suggest that high quality solutions can be achieved within an acceptable CPU time. We also project that our findings can be of general interest for other personnel scheduling problems, especially during emergency scenarios such as those related to Covid-19 pandemic.
2021
4-ott-2020
15
4
1385
1396
Personnel scheduling during Covid-19 pandemic / Zucchi, Giorgio; Iori, Manuel; Subramanian, Anand. - In: OPTIMIZATION LETTERS. - ISSN 1862-4472. - 15:4(2021), pp. 1385-1396. [10.1007/s11590-020-01648-2]
Zucchi, Giorgio; Iori, Manuel; Subramanian, Anand
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1211479
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