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MCPLP - The Maximal Covering Prevention Location Problem

This project will provide the code and data from my dissertation, circa 2010

"A Game Theoretic Approach to the Maximal Covering Prevention Location Problem" Benjamin Spaulding, University of Connecticut, 2010

What is the MCPLP?

Here is a brief description from my dissertation -

"The Maximal Covering Prevention Location Problem (MCPLP) was developed to identify which facilities, if removed, would have the greatest impact in terms of demand not covered, after an interdiction event. The MCPLP, will locate a set of facilites in such a manner that if any of them are removed the remaining coverage will be as great as possible. There is always the possiblity that an interdiction will not take place, therefore the MCPLP will also need to locate the initial set of facilities in such a manner that they cover as much as demand as possible. (Spaulding, 2010, p. 43)"

Project Goal

The goal is to translate the original code I wrote, which was in FORTRAN, into python, and to change the data inputs, so that they can be built on the fly. The end result is an updated interpretation of my work, which would potentially be easier to expand moving forward.

Why Now?

I have been sitting on this work for close to six years. As I was finishing my graduate research I got a job and moved out of Connecticut and unfortunately I never really followed up on my work that I had spent years working on with Dr. Robert Cromley. In 2016 I one of my biggest personal goals was to get better at what I do. This project is apart of my personal goals for this year! I thought github would be a great place for me to rebuild this project and share it with the world.


I am pulling a lot of stuff from different locations to compile and rebuild this project, so it's going to be a little while before I have this fully up and running.


The code from my dissertation, circa 2010



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