NCAA Class Madness Scheduling 2023 Version (V.1) Each year, there are many complaints about how the NCAA Mens Basketball Committee seeds and schedules teams in the 68-team single elimination tournament to determine the National Champion. It is inevitable that somebody is unhappy. We will approach a portion of the task by using our modeling skills to generate an alternative schedule that will likely differ from the actual assignments. Your task is twofold 1) generate a model that solves the situation using OUR parameters (which is basic scheduling common sense IMO) and then 2) do a thorough comparison of the actual tournament assignments and the results of your model. The task: Create an LP model that will assign teams to regions. You will be using only the top 24 teams (the #1 thru #6 seeds) and all 4 regions. The objective of your model for assigning teams will be to minimize the sum of distance from the location of each team to their assigned region. Distance data is provided on a separate spreadsheet. The restrictions for team assignment to regions follow below. These are in the spirit of common sense and the NCAA tournament committee rules, but more much holistic then their micro approaches. 1) Each of the four regions (South Louisville, East New York, NY, Midwest KCMO, West Las Vegas) will have exactly one #1 seed assigned, exactly one #2 seed assigned, exactly one #3 assigned, exactly one #4 assigned, exactly one #5 assigned and exactly one #6 assigned. 2) Teams from the same conference cannot be assigned to the same region (unless there are more than 4 teams from the same conference the B12 in our case). Conferences are shown on the data file (it is a team attribute). Also, dont worry about conferences that do not have multiple teams (i.e., IGNORE THEM!!!). For the B12 make sure each region has at least 1 B12 team, but no more than 2 B12 teams assigned. 3) Marquee Low Value Q There are 7 teams that have a Q factor they are non marquee teams or teams that do not have wide ranging interest of the basketball fanbase. This is scaled on a value of 1-7, but were not using that information. Just make sure each region has at least 1 team with a Q factor, but no more than 2 teams with a Q factor. 4) Seed #1 Mileage Add constraints that keep the assignment distances for the #1 Seeds to be less than the #2 seeds, the #3 seeds, the #4 seeds, the #5 seeds and the #6 seeds individually. This will also help you with Part B of the scenario. Part A - THE MODEL - Implement an appropriate linear programming model that assigns the 24 teams to Regions, minimizing the sum of overall distances subject to the items listed above.

Suggestion: Attack modularly AND model efficiently. What do we mean efficiently? If you are a little sloppy with your constraints, or include unnecessary or duplicative constraints, you may exceed the 100-constraint limit imposed by the Solver. Model carefully. Part B - THE COMPARISON: Compare your solution to the NCAAs assignments. Keep in mind neither model is necessarily better and each approach is using different criteria. NOTE: Dont just forget this part. At least 20% of your grade will be based on a thorough comparison of your model solution to the NCAA actual bracket. Specifically, measure the following for both your solution and the actual assignments (obviously, only the 24 teams of interest). - Miles overall and individually for the #1 seeds, #2 seeds, #3 seeds, #4 seeds, #5 seeds, and #6 seeds. Note here whether the #1 seeds travel less than the others (your model this should be yes). - The number of regions where multiple teams from the same conference are assigned (do not consider the B12). (Your solution should have a measure of 0). - The number of regions where the B12 assignments (at least 1 but no more than 2) are violated (Your solution should have a measure of 0). - The number of regions that do NOT satisfy the minimum number of marquee teams requirement (Your solution should have a measure of 0). A simple summary of the team assignments in a nice understandable format would also be helpful. NOTE: The data file shows the actual NCAA assignments in yellow. NOTE2: If I have errors in the data file, I reserve the right to correct them all the way up into the checkpoint deadline. I have triple teamed my typing, but that doesnt mean I havent had a turnover!