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dc.contributorDepartment of Industrial and Systems Engineeringen_US
dc.creatorHon, Wai-ting-
dc.identifier.urihttps://theses.lib.polyu.edu.hk/handle/200/3253-
dc.languageEnglishen_US
dc.publisherHong Kong Polytechnic University-
dc.rightsAll rights reserveden_US
dc.titleOptimizing patrol force utilization by genetic algorithmen_US
dcterms.abstractOver the past few years, the role of the police has been changing, as the public's expectations on police work has increased. The public do not expect police just to catch thieves. Instead, they now demand a much broader and more service oriented service scope, which includes dealing with issues like family violence. The Hong Kong police force is one of the finest forces in the world; there are around 30,000 disciplined staff working in different departments. About half of them belong to the uniform bureau whose main duty is street patrol where they provide immediate response and crime prevention. This force is facing two big challenges: increasing crime rates and manpower shortage. The purpose of this study is to find a systematic method to improve the utilization of patrol allocation. First, this study, reviews empirical research. Then, it develops a mathematical model that suits Hong Kong and discusses the implementation details. Lastly, it presents a case study to show how the optimal allocation was determined and compares it with the current allocation. The result shows that the utilization of the optimal allocation is 2% better than the estimated current allocation. There is still room for resource re-allocation.en_US
dcterms.extentix, 130 leaves : ill. ; 30 cm.en_US
dcterms.isPartOfPolyU Electronic Thesesen_US
dcterms.issued2008en_US
dcterms.educationalLevelAll Masteren_US
dcterms.educationalLevelM.Sc.en_US
dcterms.LCSHHong Kong Polytechnic University -- Dissertations.en_US
dcterms.LCSHHong Kong Police Force.en_US
dcterms.LCSHPolice patrol -- China -- Hong Kong -- Mathematical models.en_US
dcterms.LCSHResource allocation -- Case studies.en_US
dcterms.accessRightsrestricted accessen_US

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Please use this identifier to cite or link to this item: https://theses.lib.polyu.edu.hk/handle/200/3253