Determining Optimal Police Patrol Areas with Maximal Covering and Backup Covering Location Models

Curtin, Kevin M.; Hayslett-McCall, Karen; Qiu, Fang

doi:10.1007/s11067-007-9035-6

Cited by 153 publications

(108 citation statements)

References 50 publications

(39 reference statements)

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“…Police department also considered the natural boundaries, such as the hills or rivers, the locations of hotspots of crime as well as the administrative boundaries, such as neighborhoods and communities [9]. The limitation of the hand drawn boundaries is that the human is limited in the number of options they can consider and in their formal evaluation of the alternatives.…”

Section: Manual Methodsmentioning

confidence: 99%

“…The assessment is particularly difficult since both workload and response times are stochastic. This inability to measure the efficiency of the districting alternatives means that manual methods are not appropriate and good computer-based methods are required in order to create district that can positively impact high-level decision making by the police [2,9].…”

Section: Manual Methodsmentioning

confidence: 99%

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Police patrol districting method and simulation evaluation using agent-based model & GIS

Zhang

Brown

2013

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Police patrols play an important role in public safety. The patrol district design is an important factor affecting the patrol performances, such as average response time and workload variation. The redistricting or redrawing police command boundaries can be described as partitioning a police jurisdiction into command districts with the constraints such as contiguity and compactness. The size of the possible sample space is large and the corresponding graph-partitioning problem is NP-complete. In our approach, the patrol districting plans generated by a parameterized redistricting procedure are evaluated using an agent-based simulation model we implemented in Java Repast in a geographic information system (GIS) environment. The relationship between districting parameters and response variables is studied and better districting plans can be generated. After in-depth evaluations of these plans, we perform a Pareto analysis of the outputs from the simulation to find the non-dominated set of plans on each of the objectives. This paper also includes a case study for the police department of Charlottesville, VA, USA. Simulation results show that patrol performance can be improved compared with the current districting solution.

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Section: Manual Methodsmentioning

confidence: 99%

Section: Manual Methodsmentioning

confidence: 99%

Police patrol districting method and simulation evaluation using agent-based model & GIS

Zhang

Brown

2013

Secur Inform

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“…Previous research in this area can be broken down into work into pre planning patrols to be directed to either deter crime (Chawathe 2007;Li and Keskin 2014) or work into positioning patrolling officers proactively for response (Curtin et al 2010). This work is discussed below.…”

Section: Related Studiesmentioning

confidence: 99%

Predictive police patrolling to target hotspots and cover response demand

2017

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Police forces are constantly competing to provide adequate service whilst faced with major funding cuts. The funding cuts result in limited resources hence methods of improving resource efficiency are vital to public safety. One area where improving the efficiency could drastically improve service is the planning of patrol routes for incident response officers. Current methods of patrolling lack direction and do not consider response demand. Police patrols have the potential to deter crime when directed to the right areas. Patrols also have the ability to position officers with access to high demand areas by pre-empting where response demand will arise. The algorithm developed in this work directs patrol routes in real-time by targeting high crime areas whilst maximising demand coverage. Methods used include kernel density estimation for hotspot identification and maximum coverage location problems for positioning. These methods result in more effective daily patrolling which reduces response times and accurately targets problem areas. Though applied in this instance to daily patrol operations, the methodology could help to reduce the need for disaster relief operations whilst also positioning proactively to allow quick response when disaster relief operations are required.

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“…In another study [36], Hefeeda and Bagheri aim to deploy a WSN for early detection of forest fires in British Columbia, Canada and formulate the problem as a node Q-coverage problem. In [37] Curtin, Hayslett-McCall, and Qiu develop a methodology to integrate Geographic Information System (GIS) with linear programming optimization for generating alternative optimal solutions. They also study the problem of locating police patrol and account for the backup coverage.…”

Section: Literature Reviewmentioning

confidence: 99%

A multi-criteria assessment of the p-median, maximal coverage and p-center location models

2017

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Original scientific paper Location problems consider locating facilities with the objective of finding their best locations. In most real world problems, it is common that a demand node is required to be covered with multiple facilities in order to ensure a backup supply. The backup supply is necessary especially for public or emergency service location problems where a covered demand may not be serviced if it's designated facility is engaged serving other demands. In this study we consider three classic location models, i.e. p-median, maximal coverage and p-center, and compare their performances with respect to seven decision criteria under Q-coverage requirement. For this purpose, we generate multiple problem instances and solve each instance with the three models for different Q-values. Our numerical results reveal the pros and cons of each model to assist decision makers in determining the most promising model with respect to each assessment criteria. Keywords: backup coverage; facility location; maximal coverage; p-center; p-median Višekriterijska procjena modela lokacije p-srednje, maksimalne pokrivenosti i p-centralnoIzvorni znanstveni članak Problemi lokacije znače lociranje objekata s ciljem pronalaženja najbolje lokacije. Kod većine stvarnih problema uobičajeno je da zahtijevani čvor zadovoljava višestruke uvjete kako bi osigurao rezervnu opskrbu. Ta je rezervna opskrba posebno potrebna kod javnih ili problema lokacije hitne službe kada se pokrivena potražnja ne može osigurati ako je njezin za to određeni objekt zauzet pružanjem usluge drugim zahtijevima. U ovom radu razmatramo tri klasična modela lokacije, t.j. p-srednje, maksimalne pokrivenosti i p-centralno, te uspoređujemo njihovo funkcioniranje u odnosu na sedam kriterija za donošenje odluke u okviru zahtjeva Q-pokrivenosti (Q-coverage). U tu svrhu generiramo slučajeve višestrukih problema i svaki slučaj rješavamo s tri modela za različite Q vrijednosti. Naši numerički rezultati otkrivaju argumente za i protiv svakog modela koji pomažu u donošenju odluke o određivanju modela koji bi najviše odgovarao u odnosu na svaki od kriterija koji se uzimaju u obzir pri donošenju procjene.

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Determining Optimal Police Patrol Areas with Maximal Covering and Backup Covering Location Models

Abstract: Maximal covering, Backup covering, Optimization, Geographic information systems, Police patrol areas, Police beats,

Cited by 153 publications

References 50 publications

Police patrol districting method and simulation evaluation using agent-based model & GIS

Police patrol districting method and simulation evaluation using agent-based model & GIS

Predictive police patrolling to target hotspots and cover response demand

A multi-criteria assessment of the p-median, maximal coverage and p-center location models

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