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台湾医院供应链系统中最优参数设置的研究。

The study of the optimal parameter settings in a hospital supply chain system in Taiwan.

作者信息

Liao Hung-Chang, Chen Meng-Hao, Wang Ya-huei

机构信息

Department of Health Services Administration, Chung Shan Medical University, No. 110, Section 1, Jian-Koa N. Road, Taichung 402, Taiwan ; Department of Medical Management, Chung Shan Medical University Hospital, No. 110, Section 1, Jian-Koa N. Road, Taichung 402, Taiwan.

Department of Applied Foreign Languages, Chung Shan Medical University, No. 110, Section 1, Jian-Koa N. Road, Taichung 402, Taiwan ; Department of Medical Education, Chung Shan Medical University Hospital, No. 110, Section 1, Jian-Koa N. Road, Taichung 402, Taiwan.

出版信息

ScientificWorldJournal. 2014;2014:967140. doi: 10.1155/2014/967140. Epub 2014 Aug 27.

DOI:10.1155/2014/967140
PMID:25250397
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4163342/
Abstract

This study proposed the optimal parameter settings for the hospital supply chain system (HSCS) when either the total system cost (TSC) or patient safety level (PSL) (or both simultaneously) was considered as the measure of the HSCS's performance. Four parameters were considered in the HSCS: safety stock, maximum inventory level, transportation capacity, and the reliability of the HSCS. A full-factor experimental design was used to simulate an HSCS for the purpose of collecting data. The response surface method (RSM) was used to construct the regression model, and a genetic algorithm (GA) was applied to obtain the optimal parameter settings for the HSCS. The results show that the best method of obtaining the optimal parameter settings for the HSCS is the simultaneous consideration of both the TSC and the PSL to measure performance. Also, the results of sensitivity analysis based on the optimal parameter settings were used to derive adjustable strategies for the decision-makers.

摘要

本研究提出了医院供应链系统(HSCS)的最优参数设置,其中将总系统成本(TSC)或患者安全水平(PSL)(或两者同时)视为HSCS绩效的衡量标准。在HSCS中考虑了四个参数:安全库存、最大库存水平、运输能力和HSCS的可靠性。采用全因子实验设计来模拟HSCS以收集数据。使用响应面法(RSM)构建回归模型,并应用遗传算法(GA)来获得HSCS的最优参数设置。结果表明,获得HSCS最优参数设置的最佳方法是同时考虑TSC和PSL来衡量绩效。此外,基于最优参数设置的敏感性分析结果被用于为决策者推导可调整策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/76b2/4163342/e651e30e614b/TSWJ2014-967140.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/76b2/4163342/9c7029466397/TSWJ2014-967140.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/76b2/4163342/7d42aba023b5/TSWJ2014-967140.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/76b2/4163342/e651e30e614b/TSWJ2014-967140.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/76b2/4163342/9c7029466397/TSWJ2014-967140.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/76b2/4163342/7d42aba023b5/TSWJ2014-967140.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/76b2/4163342/e651e30e614b/TSWJ2014-967140.003.jpg

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