Introduction

This Workforce Scheduling demo addresses an important problem in the services industry: How to create shift schedules that maximize resource utilization.

Workforce Scheduling entails assigning shifts to personnel from a service company, like a restaurant, in order to cover the demand for resources, which fluctuates over time. In this demo, 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.

 

Workforce Scheduling Problem

Consider a service business, like a restaurant, that creates its workforce plans for the next two weeks (or 14 days). The workers are only required to have one set of skills. There are a number of workers with the same set of skills and with identical productivity who are available to work on some of the days during the two-week planning horizon. There is only one shift per workday. Each shift may have different resource (worker) requirements on each workday.

The service business may hire extra (temp) workers from an agency to satisfy shift requirements. The service business wants to minimize the number of extra workers they need to hire and – to achieve the secondary objective of “fairness” – it wants to balance the workload of employed workers.

 

Solution Approach

This workforce scheduling problem is modeled as a MIP (mixed-integer programming) problem with multiple objective functions. We use a hierarchical approach to tackle this multi-objective optimization problem.

 

Consider a scenario where the restaurant has eight employed workers. The planning horizon is two-weeks. We illustrate an optimal solution to this problem considering the resource requirements on each day of the planning horizon and the availability of the eight employed workers. Notice that to satisfy demand, some extra workers are required on some days of the planning horizon.

 

Access the Workforce Scheduling Problem

To access the Workforce Scheduling Problem 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.

Guidance for Your Journey

Gurobi: Always Free for Academics

We make it easy for students, faculty, and researchers to work with mathematical optimization.

Trusted Partners, at Your Service

When you face complex optimization challenges, you can trust our Gurobi Alliance partners for expert services.

We’ve Got Your Back

Our global team of helpful, PhD-level experts are here to support you—with responses in hours, not days.

What's
New at Gurobi

News
Gurobi 10.0 Delivers Blazing-Fast Speed, Innovative Data Science Integration, and an Enterprise Development and Deployment Experience
Latest release enables data professionals to easily integrate machine learning models into optimization models to solve new types of problems.
 Learn More
Event
Webinar: What’s New in Gurobi 10.0
In this webinar, attendees will get a first look at our upcoming product release, Gurobi 10.0. We will summarize the performance improvements and highlight some of the underlying algorithmic advances, such as the network simplex algorithm, enhancements in concurrent LP, and optimization based bound tightening.
 Learn More
new content
Cost Savings & Business Benefits for Gurobi Customers
2022 Total Economic Impact™ Study Reveals A 518% ROI with Gurobi
 Learn More