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The newsvendor model revisited： the impacts of high unit holding costs on the accuracy of the classic model

Frontiers of Business Research in China 2018年第2期12卷 141-154页

作者： Shaolong Tang Stella Cho Jacqueline Wenjie Wang Hong Yan Division of Business and Management Beijing NormalUniversity-Hong Kong Baptist University United International College 2000 JinTong RoadTangjiawan Zhuhai Guangdong China

The newsvendor problem has been applied in various business settings. It is often assumed that the decision variable, i.e., order-up-to level, has no impacts on the holding costs for average inventory cycled in a given period, which is the difference between beginning and ending inventory levels on hand in that period. The average holding cost for this portion of inventory is conveniently and approximately calcutated as half the product of the unit holding cost and the expectation of the demand in one period if it is assumed that the inventory is approximately evenly consumed. It is a good approximation when the unit holding cost is significantly lower than the unit backorder cost as this optimal solution to inventory level is able to guarantee a low probability of understocking. However, if this condition does not hold, the approximation may deviate from the actual cost and cannot measure the expected holding cost for this portion of inventory. This paper examines the impact of the cycle stock holding cost on the newsvendor model and the conditions under which this portion of cost is not negligible.

关键词： Newsvendor model Inventory control Stochastic model

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Guest Editorial for Special Issue on Time Series Classification

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IEEE/CAA Journal of Automatica Sinica 2019年第6期6卷 1291-1292页

作者： Houshang Darabi Georgiana Ifrim Patrick Schafer Diego Furtado Silva Department of Mechanical and Industrial Engineering University of Illinois at Chicago(UIC) university of Bucharest Romania university of Berlin Sciences(ICMC) University of Sao Paulo

TIME series classification research and applications have recently received a lot of *** the rapid advancement of technological devices,time series data are being collected by a wide variety of devices,resulting in a wide range of research and *** fields of studies,ranging from healthcare to weather readings,require time series *** and action recognition using time series data from fitness trackers are commonly being ***,a new generation of algorithms and techniques are being used to classify time series data that are extensively available to the research *** example,recently deep learning techniques that utilize convolutions and recurrent neural networks are being used to classify epileptic seizures from EEG recordings made available at the university of California-Irvine data repository.

关键词： classify utilize recording

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