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    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/78120


    Title: 警察勤務人力供給規劃之研究;Police Officer Duty Manpower Supply Planning
    Authors: 顏上堯
    Contributors: 國立中央大學土木工程學系
    Keywords: 例行性警察人力供給模式;預期性事件警察人力供給模式;隨機性需求;數學規劃;啟發解法;;Routine police officer manpower supply planning model;Anticipated police officer manpower supply planning model;Stochastic-demand;Mathematical programming;Heuristic.
    Date: 2018-12-19
    Issue Date: 2018-12-20 10:56:57 (UTC+8)
    Publisher: 科技部
    Abstract: 良好的警察人力供給規劃,可使分局各派出所精確地安排每日各班次之人力供給量,有效達到每日之警力配置需要。目前的警察人力供給規劃主要依決策者的經驗,以人工方式進行規劃,除缺乏效率外,亦難以掌握規劃的品質,往往導致不當的人力供給規劃。另外,各派出所的人力供給規劃上,目前係獨立進行,派出所間較缺乏互相支援的規劃,在現有不足的人力資源下,常導致人力的供給規劃困難。因此,如何建立有效的警察人力供給策略,並針對例行性與預期性事件的人力供給規劃,發展最佳化模式,將是有效運用警察分局下各派出所人力之一重要課題。本研究擬針對短期人力供給規劃問題,以系統最佳化觀點,考量警察分局下派出所實務狀況和不同人力供給方式,發展二個確定性需求與二個隨機性需求之例行性警察人力供給規劃模式。另外,本研究亦考量警察局之交通警察大隊下直屬分隊與附屬至各分局下的配賦分隊、保安警察大隊下的保安中隊、各分局內勤組、分局下的警備隊與各派出所實務狀況,及其人力供給上限等限制,發展確定性與隨機性需求之預期性事件警察人力供給規劃模式。由於本研究內容的範圍頗大,故分為三年期研究計畫分別探討。在第一年期研究計畫中,本研究擬假設各派出所每日例行性勤務的人力需求量已知且確定,考量實務相關限制以及不同人力供給方式及總人力供給小時最小化目標下,利用數學規劃方法,分別建立基本及相互支援供給方式下二個確定性需求之例行性警察人力供給模式,以決策出各派出所每日各班次之人力供給量。本研究擬先利用CPLEX軟體進行求解,如求解效率不佳,再依問題特性發展啟發解法求解。在第二年期研究計畫中,本研究擬以第一年確定性模式為基礎,考量現實每日勤務人力的隨機需求現象,修正人力需求量為隨機值,分別建立基本及相互支援供給方式下二個隨機性需求例行性警察人力供給模式,並擬運用問題分解技巧及確定性模式解法發展啟發解法,以求解二隨機模式。在第三年期研究計畫中,本研究擬以常見之集會遊行事件為研究對象,考量事件勤務人力之確定及隨機需求量、與警政相關單位之人力供給限制下,分別發展確定性及隨機性需求下預期性事件警察人力供給規劃模式。本研究擬先利用CPLEX軟體求解此二模式,如求解效率不佳,再依問題特性發展啟發解法求解二模式。本研究期望所發展的模式及求解方法除能提供學術界參考之外,更能提供警政單位進行有效的警察人力供給規劃,幫助警政單位提升人力供給配置之效力。 ;A good police officer manpower supply plan helps departments arrange more precisely manpower supply for each work shift to meet the daily demand. However, currently the police officer manpower supply plans for police departments/divisions in Taiwan are typically generated with decision maker experiences, which are neither efficient nor effective. It is difficult to control the planning quality, usually resulting in inadequate manpower supplies. In addition, currently each station of a police division for most departments in Taiwan generally performs the manpower supply planning independently, without considering mutual support between stations. Hence, how to build the police officer manpower supply strategies under scarce human resources, and to develop routine and anticipated manpower supply models, are very important issues for police divisions/departments to efficiently use their manpower. In this study, two routine deterministic-demand and two routine stochastic-demand police officer manpower supply planning models for the short-term operation are developed from a system optimization point of view, considering different manpower supply strategies and real practices for a police division. In addition, an anticipated deterministic-demand and an anticipated stochastic-demand police officer manpower supply planning models are developed by considering different manpower supply strategies and real practices for a police division. Because the content of this study is large, the study is divided into a three-year project.In the first year, we will adopt the mathematical programming method to develop two routine deterministic-demand police officer manpower supply models, a basic model and a mutual support model, by considering different supply strategies and related operating constraints, with the objective of minimizing total manpower supply-hours, given that the daily demand for routine duties is known and fixed, to determine the work shifts and the associated daily manpower supplies. Since both models’ problem sizes are medium, we will first try to utilize the CPLEX, a mathematical programming solver, to solve the deterministic models. If it is inefficient to solve the two models, we will develop heuristics according to the problem characteristics. In the second year, we will develop two routine stochastic-demand police officer manpower supply planning models by modifying the fixed demands in the corresponding deterministic-demand models. We will adopt the problem decomposition technique and the method for solving deterministic-demand models to develop heuristics to efficiently solve the two stochastic models. In the third year, focusing on large-scale events we will consider the demand constraints and related supply constraints to construct an anticipated deterministic-demand police officer manpower supply model, and then to develop an anticipated stochastic-demand manpower supply planning model by modifying the fixed demand parameters in the deterministic-demand model. CPLEX will first be used to solve the two models. If it is not efficient, then we will develop a problem-oriented heuristic to efficiently the two models. Finally, beside the contribution to the academics, these models with the solution methods are expected to be useful for police departments/divisions to generate optimal manpower supply plans, so as to reduce the shortage of police officers and improve the performance in managing the police officer human resources.
    Relation: 財團法人國家實驗研究院科技政策研究與資訊中心
    Appears in Collections:[土木工程學系 ] 研究計畫

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