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New AI framework optimizes delivery routes and dynamic pricing

Researchers have developed GREAT-ESDD, a novel framework that uses a Graph Edge Attention Network (GREAT) to optimize delivery routes and dynamic pricing for scenarios involving both home and out-of-home delivery options. This system aims to reduce costs by reoptimizing routes in real-time and steering customers towards out-of-home deliveries when home delivery would be more expensive. By employing Thompson sampling to learn customer preferences, GREAT-ESDD demonstrated an approximate 11% increase in profit compared to traditional routing solvers within a similar pricing decision time budget. AI

IMPACT This research could lead to more efficient logistics and personalized pricing strategies in the delivery industry.

RANK_REASON The cluster describes a new academic paper detailing a novel AI method for a specific problem. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

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New AI framework optimizes delivery routes and dynamic pricing

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The cluster describes a new academic paper detailing a novel AI method for a specific problem. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Attila Lischka (Jeff), Ze Zhou (Jeff), Xuegang (Jeff), Ban, Bal\'azs Kulcs\'ar ·

    GREAT-ESDD: Graph Edge Attention Network for Effectively Steered Delivery Decisions

    arXiv:2610.14792v1 Announce Type: new Abstract: Online, same-day delivery requires operators to constantly update their routes, and the routing cost for deliveries increases with the number of customers. Out-of-home (OOH) delivery options can help companies handle increasing cust…