Modeling Alabama Tornado Emergency Relief (MATER)

Modeling Alabama Tornado Emergency Relief (MATER) Joe Cordell Spencer Timmons Michael Fleischmann

Overview • Background • Problem Abstract • Network Overview (Nodes, Arcs) • Mathematical Model • Scenarios • Results • Conclusions • Further Work • Video Link

Background • State of Alabama • Major Cities: Birmingham, Montgomerey, Huntsville, Mobile, Tuscaloosa • Population: 4.7 million • Average 23 Tornados Per Year • $13 million in average annual damages

Background • Tornado Outbreak on April 27th 2011 • 165 tornados across the United States • 248 fatalities • Over $16 billion in damages over 3 days • Listed by NOAA as the fourth deadliest in United States history

April 27th, 2011 – Tornados • 62 Tornados in Alabama alone • 2219 injuries • 192 fatalities • Only the second day in history that there were three or more F5 or EF5 tornadoes.

Background • Cordova • Population: 2260 • Two tornados • Four fatalities

Problem Abstract • Relief supply flow as a Min-Cost Flow Model • Goal: To supply damaged cities in the least amount of time and determine if prepositioning of supplies will affect total travel time • Key modifications to the basic model • Randomized delay • Interdiction represented by arc delays • Measures of Effectiveness: • Total travel time • Access to damaged cities

Nodes Huntsville Birmingham Tuscaloosa

Arcs Huntsville Birmingham Tuscaloosa

Abstract Network

April 27th, 2011 – Tornados We Modeled Jasper, AL Area

Mathematical Model MIN-COST FLOW Objective: Move humanitarian supplies to damaged towns in shortest time where costs are hours of movement required to deliver supplies. There is a demand for supplies at each damaged town. MATER looks at worst case scenario by implementation of a “smart” tornado which seeks to damage roads so as to inflict the greatest cost on the operator. C=24 City C=0 s t AirPort C=5 City C=20

Mathematical Model MIN-COST FLOW Objective: Move humanitarian supplies to damaged towns in shortest time where costs are hours of movement required to deliver supplies. There is a demand for supplies at each damaged town. MATER looks at worst case scenario by implementation of a “smart” tornado which seeks to damage roads so as to inflict the greatest cost on the operator. C=50 C=24 City 1 C=0 s t AirPort C=5 City -1 C=20

Scenario 1aDestroyed Roads-Jasper Only Damaged City City Node Airport Node

Scenario 1bDestroyed Roads-Jasper and Blount Springs Damaged City City Node Airport Node

Scenario 1cDestroyed Roads-Jasper, Blount Springs and Oneonta Damaged City City Node Airport Node

Scenario 1cDestroyed Roads-Jasper and Blount Springs Damaged City City Node Airport Node

Scenario 2cDelays Roads-Jasper, Blount Springs and Oneonta Damaged City City Node Airport Node

Scenario 2c Delays Roads-Jasper, Blount Springs and Oneonta Damaged City City Node Airport Node

Scenario 3Prepositioned Aid Damaged City Prepositioned Stocks City Node Airport Node

Modeling Alabama Tornado Emergency Relief (MATER)