Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.551299
Title: Improving police efficiency to meet demand issues
Author: Edleston, O. S. S. T.
Awarding Body: Loughborough University
Current Institution: Loughborough University
Date of Award: 2010
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Abstract:
Demand modelling and simulation techniques are used in many industrial practices in order to be able to effectively manage the utilization of available resources. The current economic climate has intensified activity within this field with particular interest being paid to any potential cost savings and other financial benefits that may be obtained. Further the creation of a realistic representation of the demands present within a system can lead to a better understanding of system behaviour; this then may facilitate the identification of elements that are likely to allow improvement to system performance through their perturbation. Within this thesis a model is constructed for the demands upon front line Police officers that are used in response to high importance calls to service from the public. Tabu search and genetic algorithms are optimizing search techniques developed and applied across a wide variety of fields. They are particularly well suited to combinatorial problems in which the ordering or arrangement of system elements has an impact upon the quality of solution as assessed by some quantifying objective function. In this thesis both of these methods are applied to the staff resource allocation problem as posed by Leicestershire Police with the strengths and weaknesses of each evaluated. Customized diversification and intensification approaches are applied to the tabu search methodology in order to improve performance through tailoring it to the specific optimization problem considered. Both search algorithms are shown to be well suited to the target problem and each result in the generation of solutions of similar quality.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.551299  DOI: Not available
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