Linear & Integer Optimization using Python PuLP and AMPL

This project explores 16 real-life optimization problems, modeling them mathematically and solving them using CBC and CPLEX solvers via AMPL software and Python's PuLP library.

GitHub

16 Problems

  1. Bluesky - Bluesky Airlines Problem PDF      Bluesky - 1-2 Bluesky Afterclass PDF
  2. Paper Recycling - SJ PDF
  3. Amazing Deal - Case PDF      Amazing Deal - Facility Location PDF Session 1&2
  4. Assembly Line Balancing - ALB Model PDF
  5. Freight Allocation - 10 Freight Allocation PDF
  6. Global Electronics - SM PDF
  7. Mars Incorporated - PDF
  8. Milk Collection - Complete PDF      Milk Collection - Complete VRP PDF
  9. Mining Problem - Mining PDF
  10. Motorola - Selection PDF
  11. Network Design - PDF      Network Design - PPT
  12. Power Generation - PPT
  13. Red Tomatoes - PDF
  14. Selecting Telecommunication Carriers - PPT
  15. Sinofert - PPT
  16. Workforce Scheduling - PDF

Linear Optimization Problems Combined

The merged PDF of all the problems can be viewed here. Preview the report below or download it.

Academic Integrity Notice

I am unable to share the Python and AMPL codes for these optimization problems as they are part of the Indian Institute of Management (IIMA) curriculum. Uploading them online would violate academic integrity policies. For further information about these problems, please contact me directly.