Skip to content

Optimized course scheduling by mixed integer programming (MIP) on Python using Gurobi package to increase classroom seat utilization rate and percentage of students taking courses in prime time

Notifications You must be signed in to change notification settings

drawning0510/Python-Course_Scheduling_Optimization

Repository files navigation

Python-Course_Scheduling_Optimization

Optimized course scheduling by mixed integer programming (MIP) on Python using Gurobi package to increase classroom seat utilization rate and percentage of students taking courses in prime time

Instruction for running the code

  1. Download both data files and Python code in the same folder
  2. Run Course Scheduling Optimization.ipynb(Gurobi license required)

File list

  1. Dataset files: Marshall_Course_Enrollment_1516_1617.xlsx, Marshall_Room_Capacity_Chart.xlsx
  2. Supporting files: Description of Project.pdf, Description of Data.pdf
  3. Python code: Course Scheduling Optimization.ipynb
  4. Output: output.xlsx
  5. Final Report: Course Scheduling Optimization Project.pptx, Final Report.pdf

Contributors

  • Ian Chi
  • Siyao Hu
  • Muhammad Musthofa
  • Yue Shi
  • Rushan Zhang

About

Optimized course scheduling by mixed integer programming (MIP) on Python using Gurobi package to increase classroom seat utilization rate and percentage of students taking courses in prime time

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published