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

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

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Afghanistan Illegal Drug Trade

LT Dan Ryan

Capt Steve Felts

Capt Bethany Kauffman

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Agenda

• Problem Statement• Background• Network• Max-Flow Interdiction Model• Conclusions• Questions

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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

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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.

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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.

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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

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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

The Network

The Network

Start

The Network

End

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Europe Resolution

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

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Full Network

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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, 2nd interdiction on an arc half as effective as the first)

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Max Flow Interdiction Model

min𝑥, w

  max𝑣 ,𝑦

   v −∑( 𝑖 , 𝑗 )

𝑑𝑖𝑗𝑦𝑖𝑗 (𝑥𝑖𝑗+0.5∗𝑤𝑖𝑗)

𝑠 . 𝑡 .     ∑ 𝑦𝑖𝑠−∑ 𝑦𝑠𝑖=−𝑣         ∑ 𝑦𝑖𝑡−∑ 𝑦𝑡𝑖=𝑣         ∑ 𝑦𝑖𝑎−∑ 𝑦𝑎𝑖=0                           𝑦𝑖𝑗≤𝑢𝑖𝑗                            0≤ 𝑦𝑖𝑗

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Penalty Calculation

-Longer distance arcs have a higher probability of interdiction, or ‘penalty’, as more drugs are likely to be seized along longer routes.

-Penalty based on great circle distances and with a constant of .1 (An interdiction team on an arc guarantees interdiction of 10% of heroin across an arc regardless of distance).

*Also calculated for 50% guaranteed interdiction

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Resiliency Curves 10% POI

0 1 2 3 4 5 6 7 8 9 100

50

100

150

200

250

10% 1 Attack10% 2 Attacks10% 1.5 Attacks (2nd Attack Half as Effective as First)

Number of Attacks

Hero

in T

rans

ited

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10% POI: 1 Attack Per Arc1attacks per arc

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10% POI: 2 Attacks Per Arc

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Resiliency Curves 50% POI

0 1 2 3 4 5 6 7 8 9 100

50

100

150

200

250

50% 1 Attack

50% 2 Attacks

50% 1.5 Attacks (2nd Attack Half as Effective as First)

Number of Intercepted Edges

Her

oin

Tran

site

d

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50% POI: 1 Attack Per Arc

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50% POI: 2 Attacks Per Arc

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Conclusions

Assuming 10% POI:

-The number of attacks performed on an edge (1, 2, or when the 2nd 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.

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Conclusions

Assuming 50% POI:

-The number of attacks performed on an edge (1, 2, or when the 2nd 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

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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

QuestionsThanks for your attention!

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