دانلود مقاله ISI انگلیسی شماره 110199
ترجمه فارسی عنوان مقاله

مدل سازی عملکرد یک زنجیره تامین دو اکسل در سطوح گوناگون به اشتراک گذاشتن اطلاعات موجود در پایگاه داده

عنوان انگلیسی
Performance modeling of a two-echelon supply chain under different levels of upstream inventory information sharing
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
110199 2017 32 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Computers & Operations Research, Volume 77, January 2017, Pages 210-225

ترجمه کلمات کلیدی
مدل های صف بندی، شبکه زنجیره تامین، اشتراک اطلاعات موجودی، سیاست پایه سهام،
کلمات کلیدی انگلیسی
Queueing models; Supply chain network; Inventory information sharing; Base-stock policy;
پیش نمایش مقاله
پیش نمایش مقاله  مدل سازی عملکرد یک زنجیره تامین دو اکسل در سطوح گوناگون به اشتراک گذاشتن اطلاعات موجود در پایگاه داده

چکیده انگلیسی

The advancement in information technology has facilitated the sharing of information in supply chain networks (SCNs), resulting in effective management of inventory and storage capacity. In this paper, our focus is on upstream inventory information sharing. Existing analytical performance evaluation models of SCNs are not capable of assessing the impact of inventory information sharing. To address this need, we develop performance evaluation models of SCNs that explicitly consider production capacity, inventory related decisions, variability, transit delays and inventory information sharing in a unified manner. We employ a two-echelon SCN configuration with two retail stores and two production facilities as a test bed. The retail stores have inventory information from the production facilities. We model three levels of inventory information sharing in our study; the information shared ranges from the stock-out information at the lowest level to inventory and backorder level information at the highest level. We develop analytical models first for Poisson arrivals and exponential processing times under all levels of inventory information sharing. We extend these models to general inter-arrival and processing time distributions and subsequently include transit delays between the production facilities and the retail stores. We demonstrate the performance prediction capability of the analytical models developed via extensive numerical experimentation.