E-Commerce Delivery Optimization: A Transportation Problem Perspective on Fulfilment-to-Hub Allocation and Last-Mile Routing

This paper reviewed two journal-level applications of OR to e-commerce logistics and found that the classical transportation problem was embedded in both as the flow of packages in the delivery network (in Article A) or the temporal arrangement of consolidations (in Article B). The base fulfilment-to-hub model was solved with all three initial assignment rules, tested with the MODI method, and interpreted through shadow prices; the optimal solution was proven to be 9.4% better than with the North-West Corner method, and the VAM was not always the best starting point. Five gaps were found in the reviewed articles: allocation benefits from shared depots, customer waiting costs, demand-side uncertainty, cost–emissions trade-offs, and returns to the origin. Five extended transportation models were found to fill these gaps: pooling depots reduced costs by 11.7% over allocation alone; a one-day delivery window reduced delivery costs by 19% net of penalties; scenario-based capacity booking reduced costs by INR 4,651 per day on average over plan-driven booking; clean vans reduced emissions by 30% for a 7.4% increase in costs; RTOs increased the cost per delivered package by 71% and rendered the base network configuration invalid. Thus, the results suggest a three-stage logistics planning process: allocate deliveries according to a transportation model with uncertain returns, consolidate the deliveries in a time-indexed model, and route them. Further research should focus on finding exact coefficients for the reviewed models and linking them into a cohesive system.

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