abstractin this study, a vendor-managed inventory model is developed for a single-vendor multiple-retailer single-warehouse (sv-mr-sv) supply chain problem based on the economic order quantity in which demands are stochastic and follow a uniform probability distribution. in order to reduce holding costs and to help balanced on-hand inventory cost between the vendor and the retailers, it is assu...

this research provides an optimization tool for use by supply chain managers in the design and operation of manufacturing- distribution networks under uncertain demand conditions. the problem under consideration consists of determining the supply chain infrastructure; raw material purchases, shipments, and inventories; and finished product production quantities, inventories, and shipments neede...

in this research, an integrated inventory problem is formulated for a single-vendor multiple-retailer supply chain that works according to the vendor managed inventory policy. the model is derived based on the economic order quantity in which shortages with penalty costs at the retailers` level is permitted. as predicting customer demand is the most important problem in inventory systems and th...

This paper addresses the effect of probabilistic selling on inventory decisions and the expected profit through demand reshaping and demand substitution. By considering a scenario with two higher-priced specific products and one lower-priced probabilistic product, we construct a new newsboy-type inventory model with demand reshaping and substitution. A simulation study is implemented to explore...

We present a platform built on large-scale, data-centric machine learning (ML) approaches, whose particular focus is demand forecasting in retail. At its core, this platform enables the training and application of probabilistic demand forecasting models, and provides convenient abstractions and support functionality for forecasting problems. The platform comprises of a complex end-to-end machin...

Due to extreme weather conditions and anomalous events such as the COVID-19 pandemic, utilities grid operators worldwide face unprecedented challenges. These unanticipated changes in trends introduce new uncertainties conventional short-term electricity demand forecasting (EDF) since its result depends on recent usage an input variable. In order quantify uncertainty of EDF effectively, this pap...