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arXiv · 2507.15282

Predict, Reposition, and Allocate: A Greedy and Flow-Based Architecture for Sustainable Urban Food Delivery

Aqsa Ashraf Makhdomi·Iqra Altaf Gillani
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Abstract

The rapid proliferation of food delivery platforms has reshaped urban mobility but has also contributed significantly to environmental degradation through increased greenhouse gas emissions. Existing optimization mechanisms produce sub-optimal outcomes as they do not consider environmental sustainability their optimization objective. This study proposes a novel eco-friendly food delivery optimization framework that integrates demand prediction, delivery person routing, and order allocation to minimize environmental impact while maintaining service efficiency. Since recommending routes is NP-Hard, the proposed approach utilizes the submodular and monotone properties of the objective function and designs an efficient greedy optimization algorithm. Thereafter, it formulates order allocation problem as a network flow optimization model, which, to the best of our knowledge, has not been explored in the context of food delivery. A three-layered network architecture is designed to match orders with delivery personnel based on capacity constraints and spatial demand. Through this framework, the proposed approach reduces the vehicle count, and creates a sustainable food delivery ecosystem.

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Aqsa Ashraf Makhdomi, Iqra Altaf Gillani. 2025-07-21. Predict, Reposition, and Allocate: A Greedy and Flow-Based Architecture for Sustainable Urban Food Delivery. https://arxiv.org/abs/2507.15282

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