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Team Members• Erin Russell: Project Manager
• Ann Yaacoub: Project Scheduler
• Evan Pope: Data Measurement
• Ziya Zhao: Data Analyst
Background Information• Purdue University Dining Courts: Tom Coleman
• Affordability Goal of “Establish a 5 year capital plan and to evaluate and provide new mission-centric revenue opportunities including food truck presentation, project team”.
• Our Goals for this semester included: o providing optimal locations for lunch (monday-friday), night
(thursday-saturday), sunday night shift, and finding optimal routes from Harrison to our optimal locations
Approach Used: Lunch and Dinner Shifts • Counted Foot Traffic: Mon-Friday (10:30-2:30PM) & Thursday-Saturday (8PM-12AM)
• Minitab Regression to determine the biggest factors that determine the number of people
• 6% of people will purchase food
Approach Used: Floyd-Warshall Algorithm
• Nodes,Arcs, Edges
• All nodes to all others
• Optimal path and optimal subpath
• Intermediary nodes
Approach Used: Minimax
• Used the equations for C1, C2, C3, C4,C5
• Found best location with respect to Rectilinear distance (P1* & P2*)
Locations Coordinates C1= min (xi+yi) C2= max(xi + yi) C3= min(-xi+yi) C4= max(-xi+yi)
McCutcheon & Harrison (2.5, 5) 7.5 7.5 2.5 2.5
Purdue Village (2.5,3.5) 6 6 1 1
Shreve & Erhart (3,5.5) 8.5 8.5 2.5 2.5
First Street Towers (2.5,5) 7.5 7.5 2.5 2.5
Meredith (4,5.5) 9.5 9.5 1.5 1.5
Windsor (4, 5.5) 9.5 9.5 1.5 1.5
Wiley & Tarkington (4.5, 7) 13.5 13.5 2.5 2.5
Owen (4.5, 8) 12.5 12.5 3.5 3.5
Cary Quadrangle (5.5, 8) 13.5 13.5 2.5 2.5
Hill Top (4, 9) 13 13 5 5
Results: Day Shift Regression
The regression equation is
Number of people = 349 - 7.3 Temperature + 434 CL50 - 661 EE and Potter
+ 838 Time + 0.223 Temp^2 - 174 Time^2
Predictor Coef SE Coef T P
Constant 348.9 443.1 0.79 0.439
Temperature -7.26 24.10 -0.30 0.766
CL50 433.8 148.3 2.93 0.008
EE and Potter -660.7 148.4 -4.45 0.000
Time 838.1 319.8 2.62 0.015
Temp^2 0.2228 0.3366 0.66 0.514
Time^2 -174.49 62.56 -2.79 0.010
S = 331.584 R-Sq = 75.9% R-Sq(adj) = 69.6%
Results: Night Shift RegressionThe regression equation is
Response = - 217 + 21.5 Temp - 141 Time + 88.7 PMU + 175 Lawson -
0.240 Temp^2 + 22.1 Time^2
Predictor Coef SE Coef T P
Constant -217.0 242.8 -0.89 0.391
Temp 21.50 15.74 1.37 0.199
Time -140.98 82.23 -1.71 0.114
PMU 88.67 31.96 2.77 0.018
Lawson 174.67 31.96 5.47 0.000
Temp^2 -0.2400 0.2130 -1.13 0.284
Time^2 22.05 16.51 1.34 0.209
S = 55.3541 R-Sq = 80.6% R-Sq(adj) = 70.0%
Results: Shortest Path
Harrison to PMU: (Node 1 to Node
38):1→9→15→21→24→27→30→33→45→46→38
Total distance:21.47
Harrison to Krannert: (Node 1 to Node
38):1→9→15→21→24→27→30→33→45→46→38
Total distance:21.47
Harrison to Lawson: (Node 1 to Node 19):1→3→2→4→7→13→19
Total distance:13.5
Conclusions and Recommendations
• Best locations: o CL50- Day shift o PMU sidewalk-- Night Shift o Near Meredith-- Sunday Night
• Things to Considero Special Events: Concerts, Farmers Market, Sports