COVID 19 Vaccine Distribution

Linear Optimization

BMGT332: Quantitative Models for Management Decisions

Final Report

	Solution	Constraints are met.

Task:

The task for this project was to build a linear optimization problem from scratch while providing a list of questions related to the problem created (similar to the textbook examples ). The problem had to be original and solved through the Microsoft Excel add-on Analytic Solver.

Challenges:

One of the largest challenges to this problem was the trial and error period. In order to make the problem as realistic as possible I did research on the specific distribution centers locations. When done, I proceed to create the composition. However, establishing price, destinations, and routes was more challenging then expected. I was faced with tough decisions such as choosing to minimize profits or miles, required quantities, and variable routes all of which altered the problem in different ways.

Outcome:

In order to overcome these challenges I ran the simulation multiple times to understand which objective was most important. For instance I began by determining which distribution centers were the largest and thus required the most vaccines. I next moved on to how each paths transportation cost would vary based on plane or truck. With countless simulations and my design thinking I was able to visualize my distribution network and put together the pieces. This network identified the price to transportation, required quantity of vaccines at each port, and the routes the simulation had to choose from.