Optimizing patrolling routes using Maximum Benefit k-Chinese Postman Problem

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dc.contributor.advisorHaghani, Alien_US
dc.contributor.authorSamimi Abianeh, Arezooen_US
dc.contributor.departmentCivil Engineeringen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.date.accessioned2015-09-18T06:04:57Z
dc.date.available2015-09-18T06:04:57Z
dc.date.issued2015en_US
dc.description.abstractProviding security and safety in urban areas is of paramount importance. The objective of this study is to find several routes for police patrolling vehicles in order to maximize the benefit based on the historical data of a given area such as crime rate. To this end, we first formulate the problem as a maximum benefit k-Chinese Postman Problem and find the optimal solutions for small size networks. We then employ the tabu search metaheuristic method to develop an algorithm that finds close to optimal solutions for the corresponding networks. A comparison between the results of the mathematical model and the metaheuristic algorithm reveals that the results are in a good agreement in terms of accuracy and the quality. The proposed algorithm is then used to find solutions for the city of College Park.en_US
dc.identifierhttps://doi.org/10.13016/M25M0D
dc.identifier.urihttp://hdl.handle.net/1903/17124
dc.language.isoenen_US
dc.subject.pqcontrolledCivil engineeringen_US
dc.subject.pqcontrolledTransportationen_US
dc.subject.pquncontrolledArc Routingen_US
dc.subject.pquncontrolledMaximum benefit Chinese Postman Problemen_US
dc.subject.pquncontrolledPatrolling vehiclesen_US
dc.subject.pquncontrolledTabu searchen_US
dc.titleOptimizing patrolling routes using Maximum Benefit k-Chinese Postman Problemen_US
dc.typeThesisen_US

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