不规则需求模式的预测与库存计划

IF 0.6 Q4 OPERATIONS RESEARCH & MANAGEMENT SCIENCE International Journal of Knowledge and Systems Science Pub Date : 2023-08-18 DOI:10.4018/ijkss.328678
Phattaraporn Kalaya, P. Termsuksawad, Thananya Wasusri
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引用次数: 0

摘要

由于需求不规律,医院药品库存经常面临短缺或过期的问题。本文提出了三种管理方法,并对它们的性能进行了比较,包括克罗斯顿方法、指数与泊松分布相结合的方法(EPD)和平均需求间隔与平均需求相结合的方法(AAD)。采用指数加权移动平均(EWMA)控制图进行预测。使用服务水平和平均库存来评估每种方法的绩效。研究表明,每种方法的服务水平取决于需求模式特征。当需求与平均需求的方差较大时,采用EWMA方法得到的服务水平最高。当需求变异性相对较低且需求偶尔出现时,Croston方法更为有效。当采用AAD方法时,应用EWMA可以提高平均库存和服务水平。
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Forecasting and Inventory Planning for Irregular Demand Patterns
Medicine inventory in hospitals always faces either shortages or expired medication problems due to irregular demand. This work proposes three management approaches and compares their performances, including the Croston method, a combination of exponential and Poisson distribution (EPD), and the average inter-demand interval combined with average demand (AAD) were studied with the order-up-to-level policy. The exponentially weighted moving average (EWMA) control chart was used with some forecasting methods. Service level and average inventory were used to evaluate the performance of each approach. The study showed that the service level of each approach depended on the demand pattern characteristics. When the variance of demand and average demand were very high, the highest service level was found from the AAD with the EWMA approach. The Croston method was found more effective when the demand variability was relatively low, and demand appeared occasionally. Applying the EWMA increased the average inventory and service level when the AAD method was used.
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来源期刊
International Journal of Knowledge and Systems Science
International Journal of Knowledge and Systems Science OPERATIONS RESEARCH & MANAGEMENT SCIENCE-
CiteScore
3.00
自引率
10.00%
发文量
18
期刊介绍: The mission of the International Journal of Knowledge and Systems Science (IJKSS) is to promote the development of knowledge science and systems science as well as the collaboration between the two sciences among academics and professionals from various disciplines around the world. IJKSS establishes knowledge and systems science as a vigorous academic discipline in universities. Targeting academicians, professors, students, practitioners, and field specialists, this journal covers the development of new paradigms in the understanding and modeling of human knowledge process from mathematical, technical, social, psychological, and philosophical frameworks. The International Journal of Knowledge and Systems Science was originally launched by the International Society of Knowledge and Systems Science, which was initiated in 2000 in Japan and founded by Prof. Y. Nakamori, Professor Z. T. Wang and Professor J. Gu in 2003 in Guangzhou. Professor Z. T. Wang was its Founding Editor.
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