Recently there has been a surge of interest in operations research (OR) and the machine
learning (ML) community in combining prediction algorithms and optimization techniques to …

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 …

In many supply chains, firms staged in upstream of the chain suffer from variance
amplification emanating from demand information distortion in a multi-stage supply chain …

When studying the vehicle routing problem, especially for on-time arrivals, the determination
of travel time plays a decisive role in the optimization of logistics companies. Traffic Internet …

We investigate a data-driven single-period inventory management problem with uncertain
demand, where large amounts of textual online reviews and historical data are accessible …

This paper considers a multi-item newsvendor problem with a capacity constraint (Z). The
problem has already been addressed in the literature using the classical newsvendor …

Blood transfusion is one of the most crucial and commonly administered therapeutics
worldwide. The need for more accurate and efficient ways to manage blood demand and …

Logistics creates tremendous economic value through supporting the trading of goods
between firms and customers, thereby improving the welfare of the society. In order to …

Inventory control aims to meet customer demands at a given service level while minimizing
cost. As a result of market volatility, customer demand is generally changing, and ignoring …

While emission tax and mandatory emission capacity regulations are widely implemented to
control greenhouse gas emissions, it remains unclear which will lead to better performance …