Abstract
The allocation of limited yet costly police resources is a daily dilemma for police commanders. More than 50% of police department costs go into patrolling operations, which include responding to emergencies and maintaining police presence in patrolling areas. This research aims to address the managerial challenges and tradeoffs that police commanders face when designing patrolling strategies: lessening the economic burden of crime prevention and maintaining high levels of public safety. The proposed framework is implemented through a mathematical framework and simulation to obtain the best patrolling strategies for the Seattle Police Department, and the simulation results show that patrol performance can be improved using the proposed framework.
| Original language | English |
|---|---|
| Article number | 7797517 |
| Pages (from-to) | 29-41 |
| Number of pages | 13 |
| Journal | IEEE Transactions on Engineering Management |
| Volume | 64 |
| Issue number | 1 |
| DOIs | |
| State | Published - Feb 2017 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 16 Peace, Justice and Strong Institutions
Keywords
- Crimes
- evolutionary algorithm
- heuristics
- multi-objective optimization
- patrolling strategies
- police
- urban security
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