Homecare Staff Schedulimg

碩士 === 國立臺灣科技大學 === 工業管理系 === 98 === Recently, the proportion of elderly people is increasing in Taiwan. Moreover, the number of elderly people living alone and people with disabilities are also increasing. For this reason, there is an urgent need for healthcare services in Taiwan. Because there are...

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Bibliographic Details
Main Authors: Hung-Li Chu, 朱宏禮
Other Authors: Vincent F. Yu
Format: Others
Language:zh-TW
Published: 2010
Online Access:http://ndltd.ncl.edu.tw/handle/10757970659092926851
Description
Summary:碩士 === 國立臺灣科技大學 === 工業管理系 === 98 === Recently, the proportion of elderly people is increasing in Taiwan. Moreover, the number of elderly people living alone and people with disabilities are also increasing. For this reason, there is an urgent need for healthcare services in Taiwan. Because there are many inconveniences or restrictions associated with nursing homes, such as facility location, availability, and eligibility, most people prefers homecare services or community healthcare services over nursing homes when they have long-term healthcare needs. Since professional skills are essential for homecare workers, most people hire homecare workers through agents or dispatching companies. This research studied the homecare worker scheduling problem. The results of this study may help the agents or dispatching companies in planning their homecare services and scheduling their homecare staffs. This research can be divided into three stages. We first defined the scope and objective of this research. In the second stage, we defined the problem and developed a mathematics programming model for the problem based on the team orienteering problem with time windows. The model also includes special temporal constraints to deal with the synchronization and precedence requirements of homecare services. In the last stage, we developed a 2-stage metaheuristic to solve the problem. An initial solution is constructed in the first stage, and then improved by a tabu search heuristic in the second stage. 56 benchmark instances were created to test the applicability and the efficiency of the proposed meta-heuristic. Conclusions and suggestions are drawn based on the results of these computational experiments.