Personnel scheduling during Covid-19 pandemic
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Personnel scheduling during Covid-19 pandemic Giorgio Zucchi1,2 · Manuel Iori3 · Anand Subramanian4 Received: 2 May 2020 / Accepted: 25 September 2020 © Springer-Verlag GmbH Germany, part of Springer Nature 2020
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. Keywords Personnel scheduling · Covid-19 · Risk · Integer programming
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Anand Subramanian [email protected] Giorgio Zucchi [email protected] Manuel Iori [email protected]
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FMB, Marco Biagi Foundation, University of Modena and Reggio Emilia, Largo Marco Biagi 10, 41121 Modena, Italy
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R&D Department, Coopservice S.coop.p.a, Via Rochdale 5, 42122 Reggio Emilia, Italy
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DISMI, Department of Sciences and Methods for Engineering, University of Modena and Reggio Emilia, 42122 Reggio Emilia, Italy
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Departamento de Sistemas de Computação, Centro de Informática, Universidade Federal da Paraíba, Rua dos Escoteiros, Mangabeira, João Pessoa, PB 58055-000, Brazil
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G. Zucchi et al.
1 Introduction Personnel scheduling problems traditionally consist of optimizing work timetables, i.e., determining the appropriate times and shifts the employees of a company should work. Several objectives can be considered, such as minimizing duty costs, maximizing productivity, or minimizing the number of employees. The solutions generated must meet different criteria, for example, maximum number of working days, maximum amount of working hours, and so on. Due to the recent Covid-19 pandemic, we introduce a novel and emerging aspect: the risk of contagion among the workers. Covid-19 is now widely known to be highly contagious, and the interested reader may refer to, e.g., [11,13,20] for further information regarding the transmission of the virus and the source of the disease, respectively. On the one hand, there is a rich body of literature on how governments can avoid the spread of pandemic diseases [e.g., 1,7,9], or how physicians can deal with certain scenarios arising in medical centers, where they are faced with a growing, sometimes even uncertain,
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