A schedule of medical resource supply orders and transit plan

碩士 === 國立中央大學 === 土木工程研究所 === 95 === A satisfactory schedule of medical resource supply orders and transit plan can help medical institutions efficiently reduce the operating cost and to promote the medical service quality. In currently Taiwanese medical institutions, the important parameters (e.g....

Full description

Bibliographic Details
Main Authors: Jian-wei Liao, 廖建韋
Other Authors: 顏上堯
Format: Others
Language:zh-TW
Published: 2007
Online Access:http://ndltd.ncl.edu.tw/handle/45248983113522990264
Description
Summary:碩士 === 國立中央大學 === 土木工程研究所 === 95 === A satisfactory schedule of medical resource supply orders and transit plan can help medical institutions efficiently reduce the operating cost and to promote the medical service quality. In currently Taiwanese medical institutions, the important parameters (e.g., the order/transit frequency, the order quantity, and the safe stock capacity) are manually determined by staff with experience. Lacking a systematic optimization analysis, this approach rather depends on the staff’s subjective judgments. Additionally, in actual operations, the demands of medical goods often change stochastically, possibly causing the original schedule to lose its optimality. It is difficult to efficiently revise the original schedule with existent resources to respond the changes. Consequently, the effect of medical system will be decreased and the operating cost be increased. Therefore, in this research, based on a medical institution’s perspective, we systematically consider the demand of goods for every time slot in all hospital departments, the stock capacity and other constraints, as well as the integrated transit plan of medical goods in the dimensions of time and space, to construct a deterministic and a stochastic medical goods order and transit scheduling model. These two models are expected to be useful planning tools for medical institutions to determine effective resource supply orders and transit schedules. We used time-space network techniques with the system optimization perspective to construct models. A simulation-based heuristic, coupled with Mathematical programming software, was further developed to efficiently solve the model. In addition, to evaluate the deterministic and stochastic scheduling models in actual operations, we developed a simulation-based evaluation method. Finally, in order to test the proposed models and solution algorithms in actual operations, we conducted a case study based on a domestic medical institution’s operating data.