Smart Logistics: Taking Inventory Optimization to the Next Level

Climate change and a shortage of truck drivers urge a paradigm shift in truck-dominated supply chains. To alleviate the pressure on truck transport, one can bundle shipments with other companies, or shift more freight to alternative transport modes, such as train or inland waterways. In this research, we will develop ordering policies to facilitate freight bundling and a modal shift to reduce the truck intensity of supply chains. To achieve this goal, three research objectives are stipulated: (1) develop ordering policies for freight bundling using one transport mode; (2) develop ordering policies for freight bundling using two transport modes; and (3) use deep reinforcement learning to improve ordering policies for freight bundling using two transport modes. With this research, we contribute to the state-of-the-art by combining the multi-modal and collaborative literature, and by providing decision-making support for multi-modal, collaborative supply chains.