Personnel scheduling during Covid-19 pandemic

Area of Science:

• Operations Research
• Industrial Engineering
• Public Health

Background:

• The Covid-19 pandemic necessitated novel approaches to workplace safety and operational continuity.
• Personnel scheduling in critical sectors like pharmaceutical distribution faced unprecedented challenges.
• Maintaining contractual working hours while implementing contagion mitigation strategies was a key concern.

Purpose of the Study:

• To develop an optimized personnel scheduling model for a pharmaceutical distribution warehouse during the Covid-19 pandemic.
• To ensure employee safety by dividing staff into mutually exclusive groups, reducing contagion risk.
• To meet contractual working time obligations for all employees.

Main Methods:

• A mixed integer linear programming (MILP) formulation was developed to address the complex scheduling constraints.
• The proposed MILP model was applied to a real-life case study in an Italian pharmaceutical distribution warehouse.
• Scalability was assessed through tests on larger, randomly generated instances using an open-source MILP solver.

Main Results:

• The optimal schedule generated by the MILP model proved superior to the company's existing schedule.
• High-quality solutions were achieved within acceptable CPU times for most tested instances.
• The model demonstrated effectiveness in balancing operational needs with pandemic-related safety requirements.

Conclusions:

• The developed MILP formulation provides an effective solution for personnel scheduling in pandemic conditions.
• The approach offers significant improvements over traditional scheduling methods in high-risk environments.
• Findings are applicable to various personnel scheduling problems, particularly during public health emergencies like Covid-19.