Personnel scheduling during Covid-19 pandemic
| Autor: | Manuel Iori, Anand Subramanian, Giorgio Zucchi |
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| Rok vydání: | 2020 |
| Předmět: |
Risk
Original Paper 021103 operations research Control and Optimization Job shop scheduling Operations research Computer science 0211 other engineering and technologies CPU time Integer programming Computational intelligence 010103 numerical & computational mathematics 02 engineering and technology Solver 01 natural sciences Working time Scheduling (computing) Scalability Personnel scheduling 0101 mathematics Covid-19 |
| Zdroj: | Optimization Letters |
| ISSN: | 1862-4480 1862-4472 |
| DOI: | 10.1007/s11590-020-01648-2 |
| Popis: | This paper addresses a real-life personnel scheduling problem in the context of Covid-19 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. |
| Databáze: | OpenAIRE |
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