A Markov Decision Process approach for balancing intelligence and interdiction operations in city-level drug trafficking enforcement. (March 2020)
- Record Type:
- Journal Article
- Title:
- A Markov Decision Process approach for balancing intelligence and interdiction operations in city-level drug trafficking enforcement. (March 2020)
- Main Title:
- A Markov Decision Process approach for balancing intelligence and interdiction operations in city-level drug trafficking enforcement
- Authors:
- Baycik, N. Orkun
Sharkey, Thomas C.
Rainwater, Chase E. - Abstract:
- Abstract: We study a resource allocation problem in which law enforcement aims to balance intelligence and interdiction decisions to fight against illegal city-level drug trafficking. We propose a Markov Decision Process framework, apply a column generation technique, and develop a heuristic to solve this problem. Our approaches provide insights into how law enforcement should prioritize its actions when there are multiple criminals of different types known to them. We prove that when only one action can be implemented, law enforcement will take action (either target or arrest) on the highest known criminal type to them. Our results demonstrate that: (i) it may be valuable to diversify the action taken on the same criminal type when more than one action can be implemented; (ii) the marginal improvement in terms of the value of the criminals interdicted per unit time by increasing available resources decreases as resource level increases; and (iii) there are losses that arise from not holistically planning the actions of all available resources across distinct operations against drug trafficking networks. Abstract : Arresting a confirmed safehouse is the priority activity in city-level. Targeting suspected safehouses is profitable with high discount factor values. Arresting the dealers is profitable with small discount factor values. Investing in advanced tracking devices can improve the law enforcement objective.
- Is Part Of:
- Socio-economic planning sciences. Number 69(2020)
- Journal:
- Socio-economic planning sciences
- Issue:
- Number 69(2020)
- Issue Display:
- Volume 69, Issue 69 (2020)
- Year:
- 2020
- Volume:
- 69
- Issue:
- 69
- Issue Sort Value:
- 2020-0069-0069-0000
- Page Start:
- Page End:
- Publication Date:
- 2020-03
- Subjects:
- Markov decision process -- Intelligence and interdiction operations -- Illegal drug supply chains -- Column generation
Planning -- Periodicals
Economic policy -- Periodicals
Social policy -- Periodicals
Planification -- Périodiques
Politique économique -- Périodiques
Politique sociale -- Périodiques
ECONOMIC PLANNING
SOCIAL PLANNING
DECISION-MAKING
361 - Journal URLs:
- http://www.sciencedirect.com/science/journal/00380121 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.seps.2019.03.006 ↗
- Languages:
- English
- ISSNs:
- 0038-0121
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 8319.576000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 12567.xml