Optimal and Order-optimal Gated Priority-based Greedy Policies for Two-layer Multi-item Order Fulfillment
arXiv:2605.25888v1 Announce Type: new Abstract: We study how an e-commerce firm should make real-time fulfillment decisions in a two-layer distribution network when multi-item customer orders arrive sequentially and future demand is unknown. The central managerial tension is whether to use scarce front distribution center (FDC) inventory to save current fulfillment cost or preserve that inventory for future orders that may be more valuable to serve locally. We formulate an adversarial online model with multiple FDCs, one regional distribution center (RDC), multi-unit multi-item orders, and ite
The increasing complexity of e-commerce logistics and the availability of advanced AI/ML techniques are driving the need for more sophisticated fulfillment strategies.
Optimizing multi-item order fulfillment in a multi-layer distribution network can significantly reduce costs and improve efficiency for large-scale e-commerce operations.
This research provides a framework for e-commerce firms to make more intelligent real-time inventory decisions, balancing immediate fulfillment with future demand preservation.
- · E-commerce logistics firms
- · Large online retailers
- · AI/ML providers for supply chain optimization
- · Inefficient warehouse operations
- · Logistics providers without advanced optimization tools
Improved profitability and customer satisfaction for e-commerce companies due to optimized inventory and fulfillment.
Increased pressure on smaller e-commerce players to adopt similar sophisticated logistics or face competitive disadvantage.
Potential for broader automation of real-time operational decision-making across various industries beyond e-commerce.
This signal links to a primary source. Continuum Brief monitors and indexes it as part of the live intelligence stream — we do not republish source content.
Read at arXiv cs.LG