Workforce scheduling problems emerge in a wide range of service delivery settings and involve the scheduling of shifts for different types of personnel including restaurant workers, hotel reservation agents, airline crew members, contact center operators, retail store workers, nurses, and police officers. Fundamentally, these problems involve creating shift schedules that maximize resource utilization while ensuring that shift labor requirements and other business constraints are satisfied.
Workforce scheduling problems can be formulated as a multi-objective mixed-integer-programming (MIP) models, implemented using the Gurobi Python API, and solved using the Gurobi Optimizer. Access the Gurobi Workforce Scheduling Jupyter Notebook and Optimization Application Demo below to see how it works.
Workforce Scheduling Optimization Application Demo
This demo entails assigning shifts to personnel from a service company in order to cover the demand for resources, which fluctuates over time. In this example, we want to minimize the number of extra workers (temps) that we may need to satisfy resource requirements and also balance the workload of employed workers.
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To access the Workforce Scheduling demo application and create your scenario using your own data from a blank template or to play with existing default scenarios, you must first register for a Gurobi website account and then view the demo.
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