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Optimizes employee assignments across a restaurant chain by finding the most cost-effective placement of skilled staff to meet varying demands while minimizing the impact of using less experienced workers.

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Employee Scheduling

Downloads AIMMS Version WebUI Version

This repository contains a functional AIMMS example model for Employee Scheduling. It demonstrates how to determine the best placement of staff across a restaurant chain, balancing skill requirements and shift availability.

🎯 Business Problem

Managing workforce schedules in a service-oriented business is a complex puzzle. This model addresses the following challenges:

  • Minimize Costs: Reducing the overall expenditure on staffing and the shortage of skilled workforce.
  • Skill Management: Ensuring that tasks requiring specific expertise are fulfilled by qualified employees.
  • Demand Satisfaction: Meeting the varying personnel needs of different restaurant locations and shifts.
  • Preference Handling: Incorporating employee job preferences to improve overall satisfaction.

📖 How to Use This Example

To get the most out of this model, we highly recommend reading our detailed step-by-step guide on the AIMMS How-to website:

👉 Read the Full Article: Employee Scheduling Guide

Prerequisites

  • AIMMS: You will need AIMMS installed to run the model. Download the Free Academic Edition here if you are a student.
  • SQLite ODBC Driver: This project uses a database for data persistence. Ensure you have the SQLite ODBC Driver installed.
  • WebUI: This model is optimized for the AIMMS WebUI, featuring editable Gantt Charts and data-dependent CSS styling.

🚀 Getting Started

  1. Download the Release: Go to the Releases page and download the .zip file from the latest version.
  2. Open the Project: Launch the .aimms file.
  3. Run the Model: Use the provided WebUI dashboards to input data, manage the database connection, and solve the optimization.

🤝 Support & Feedback

This example is maintained by the AIMMS User Support Team.


Maintained by the AIMMS User Support Team. We optimize the way you build optimization.

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Optimizes employee assignments across a restaurant chain by finding the most cost-effective placement of skilled staff to meet varying demands while minimizing the impact of using less experienced workers.

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