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Afghanistan Illegal Drug Trade LT Dan Ryan Capt Steve Felts Capt Bethany Kauffman.

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Presentation on theme: "Afghanistan Illegal Drug Trade LT Dan Ryan Capt Steve Felts Capt Bethany Kauffman."— Presentation transcript:

1 Afghanistan Illegal Drug Trade LT Dan Ryan Capt Steve Felts Capt Bethany Kauffman

2 Agenda 2 Problem Statement Background Network Max-Flow Interdiction Model Conclusions Questions

3 Problem Statement Analyze the unimpeded flow of drugs across the global drug trade network Identify optimal locations to place drug interdiction resources Evaluate the expected impact of these interdiction strategies M 3

4 Backstory Afghanistan produces 84% of the world’s heroin and opium supplies. Profits from illegal drug sales fund criminal activities detrimental to Afghan and Global security Illegal drugs from Central Asia supply consumer demands in North America and Europe- adding to illegal drug use and dependencies harmful to society. M 4

5 Backstory Other main beneficiaries of the trade include international criminal organizations in Europe, Asia, and elsewhere. Curtailing the illegal drug trade will reduce violence among traffickers and reduce profits that fund far-reaching criminal activities. M 5

6 Data -UN Office on Drugs and Crime  World Drug Reports 2010, 2011, 2012  Global Afghan Opium Trade, A Threat Assessment  Heroin: Data and Analysis  Illicit Drug Trends in Central Asia -Interpol -Geopium P 6

7 Additional Notes Considered data from both 2002-2008 and 2009, however 2009 data did not provide constructive results compared to the 2002- 2008 data set, which was more robust Emplacing an interdiction team on an edge represents an ‘Attack’ on the edge 7

8 The Network

9 Start

10 The Network End

11 Europe Resolution Divided Western Europe into 5 individual nodes to provide further resolution to the network: Italy, Germany, France, UK, Netherlands 11

12 Full Network 12

13 Building the Model Design Stages: -Max Flow Interdiction (constant penalty, 1 interdiction per arc) -Max Flow Interdiction (non-constant penalty, 1 interdiction per arc) -Max Flow Interdiction (non-constant penalty, 2 interdictions per arc) -Max Flow Interdiction (non-constant penalty, 2 interdictions per arc, 2 nd interdiction on an arc half as effective as the first) 13

14 Max Flow Interdiction Model 14

15 Penalty Calculation 15

16 Resiliency Curves 10% POI 16

17 10% POI: 1 Attack Per Arc 17 1attacks per arc

18 18 10% POI: 2 Attacks Per Arc

19 Resiliency Curves 50% POI 19

20 20 50% POI: 1 Attack Per Arc

21 21 50% POI: 2 Attacks Per Arc

22 Conclusions Assuming 10% POI: -The number of attacks performed on an edge (1, 2, or when the 2 nd attack is half as effective as the first) is almost inconsequential with less than 5 attacks. -When multiple attacks per edge are allowed, the benefits of each additional attack is nearly linear. P 22

23 Conclusions Assuming 50% POI: -The number of attacks performed on an edge (1, 2, or when the 2 nd attack is half as effective as the first) is again almost inconsequential with less than 4 attacks. -When multiple attacks per edge are allowed, the benefits of each additional attack is nearly linear up to 4 attacks as well. -After 4 attacks, the value of each attack (or the amount of drugs interdicted) decreases substantially P 23

24 Future Work Modeling drug traffickers best responses- creating new nodes and routes (edges) Increasing resolution within the model- i.e. identifying more intermediate nodes along the routes 24

25 Questions Thanks for your attention! P


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