Models for Allocating Police Preventive Patrol Effort

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Abstract
This paper develops models that maximize the expected number of occasions per unit of time that a police patrol unit enters a street segment during the time that a crime is visible. Constraints are added that insure a minimum patrol coverage to all streets. The successive visits from street-to-street form a Markov chain. The solution that maximizes the objective function gives a stochastic decision rule which is used with Monte Carlo techniques to generate a random patrol schedule. The problem is posed with one car and several cars patrolling the same region.

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