| dc.description.abstract | Supply Chain Planning including Demand Planning and Supply Planning is one of the
most critical steps which decides the overall performance of supply chain. Especially,
new century of big data extracted from complex behaviors of customers and intense
competition between players in the same fields has motivate many companies make
investment to improve supply chain planning process. At the same time, the potential
growth of Machine Learning algorithms and optimization techniques has allowed
experts and researchers to apply these techniques in sales forecasting as well as make
approriate inventory plan to satisfy the market demand. This paper aims to fullfill three
main goal. Firstly, this paper proposes a sales prediction model using Gradient Boosting
method, paying attention to products’ perishability and profitability in feature
engineering process. Secondly, an optimal inventory ordering policy shall be designed
with the consideration in discount quantity policies and remaining shelf-life requirement
from customers. Finally, some solutions from the perspectives of business acumen will
be proposed in addition to engineering solutions so as to provide a full picture of supply
chain risk management for perishable goods.
In this work, the proposed solution is applied for ILY Company – a new player in FMCG
índustry which is seeking for cost optimization opportunities. | en_US |
