[HTML][HTML] Forecasting: theory and practice
Forecasting has always been at the forefront of decision making and planning. The
uncertainty that surrounds the future is both exciting and challenging, with individuals and …
uncertainty that surrounds the future is both exciting and challenging, with individuals and …
[HTML][HTML] Inventory–forecasting: Mind the gap
We are concerned with the interaction and integration between demand forecasting and
inventory control, in the context of supply chain operations. The majority of the literature is …
inventory control, in the context of supply chain operations. The majority of the literature is …
RNN/LSTM with modified Adam optimizer in deep learning approach for automobile spare parts demand forecasting
KK Chandriah, RV Naraganahalli - Multimedia Tools and Applications, 2021 - Springer
The spare parts demand forecasting is very much essential for the organizations to minimize
the cost and prevent the stock outs. The demand of spare parts/car sales distribution is an …
the cost and prevent the stock outs. The demand of spare parts/car sales distribution is an …
[HTML][HTML] Intermittent demand forecasting for spare parts: A Critical review
Spare parts demand forecasting has received considerable attention over the last fifty years
as it is a challenging problem for many companies. This paper provides a critical review and …
as it is a challenging problem for many companies. This paper provides a critical review and …
Comparison of statistical and machine learning methods for daily SKU demand forecasting
Daily SKU demand forecasting is a challenging task as it usually involves predicting
irregular series that are characterized by intermittency and erraticness. This is particularly …
irregular series that are characterized by intermittency and erraticness. This is particularly …
Deep reinforcement learning for selecting demand forecast models to empower Industry 3.5 and an empirical study for a semiconductor component distributor
A semiconductor distributor that plays a third-party role in the supply chain will buy diverse
components from different suppliers, warehouse and resell them to a number of electronics …
components from different suppliers, warehouse and resell them to a number of electronics …
[HTML][HTML] Using supervised machine learning for B2B sales forecasting: A case study of spare parts sales forecasting at an after-sales service provider
In this paper, we present a method to use advance demand information (ADI), taking the
form of request for quotation (RFQ) data, in B2B sales forecasting. We apply supervised …
form of request for quotation (RFQ) data, in B2B sales forecasting. We apply supervised …
Forecasting intermittent demand for inventory management by retailers: A new approach
The forecasting of intermittent demand is a complex task owing to demand fluctuations and
interval uncertainty. Intermittent demand is essentially random demand with a high …
interval uncertainty. Intermittent demand is essentially random demand with a high …
Improving sporadic demand forecasting using a modified k-nearest neighbor framework
Forecasting sporadic or intermittent demand presents significant challenges in supply chain
management, primarily due to the frequent occurrence of zero demand values and the …
management, primarily due to the frequent occurrence of zero demand values and the …
Intermittent demand forecasting for spare parts in the heavy-duty vehicle industry: a support vector machine model
Intermittent demand occurs commonly for spare parts in the heavy-duty vehicle industry.
Demand uncertainty and intermittency pose challenges to demand forecasting by …
Demand uncertainty and intermittency pose challenges to demand forecasting by …