/Homeless-Shelter-Optimization

Final Group Project for MGSC 662 - Decision Analytics as part of the MMA program at McGill University

Primary LanguageJupyter Notebook

Homeless-Shelter-Optimization

For the final project for the course, MGSC 662: Decision Analytics, my team and I created an optimization model for determining the best locations for new homeless shelters on Montreal Island. Homelessness has become a growing issue in Montreal since 2018 and we thought this was an impactful problem to tackle. To perform the analysis, we gathered data from Stats Canada, financial statements from CharityData.ca and various news articles. After gathering data we implemented an optimization model to distribute homeless people to simulate where homeless people would be located. Then we implemented a second optimization model to determine the best location for new homeless shelters to account for the unallocated homeless individuals. More detailed information on the process can be found in the Team1_MGSC662_Project.pdf.

Below are a description of the files in the repository:

  • Team1_FinalProject.xlsx: Contains raw data on existing homeless shelters, homeless population locations, and new potential homeless shelter locations
  • Final_Model.ipynb: Contains the code to process the raw data and implement both of the optimization models
  • Team1_MGSC662_project.pdf: The final report where we explain the background, rationale, model formulation, results and conclusions of the project
  • Team1_Final Presentation.pptx: The slides used to present our results to the class