An optimization-based framework for personal scheduling during pandemic events

被引：0

作者：

Hahn, Flávio Oscar ^{[1
]}

Nogueira, Bruno ^{[1
,2
]}

Pinheiro, Rian Gabriel S. ^{[1
]}

机构：

[1] Federal University of Alagoas, Brazil

[2] University of Pernambuco, Brazil

来源：

Journal of the Brazilian Computer Society | 2024年 / 30卷 / 01期

关键词：

COVID-19; Integer programming; Pandemic; personal scheduling;

D O I：

10.5753/JBCS.2024.3589

中图分类号：

学科分类号：

摘要：

In recent years, companies have faced the challenge of adapting to new guidelines and strategies aimed at preventing and reducing the transmission of COVID-19 within the workplace. An essential aspect of this adaptation is effectively managing the workday schedule to minimize social contact. This paper introduces a comprehensive optimization framework designed to automate the planning of employee schedules during pandemic events. Our framework utilizes integer linear programming to establish a set of general constraints that can accommodate various types of distancing restrictions and cater to different objective functions. To employ the framework, a company simply needs to instantiate a subset of these constraints along with an objective function based on its specific priorities. We conducted tests on our scheduling framework within three distinct real-life companies, yielding promising results. Our approach successfully increased the number of in-person workers by 15%, all while adhering to the social distancing restrictions mandated by these companies. Furthermore, the solutions generated by our method were implemented and validated within these organizations. © 2024, Brazilian Computing Society. All rights reserved.

引用

页码：143 / 154

页数：11

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