English(EN) GREAT-ESDD: Graph Edge Attention Network for Effectively Steered Delivery Decisions

新AI框架优化配送路线和动态定价

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-15 04:00

研究人员开发了GREAT-ESDD，一个新颖的框架，它使用图边注意力网络（GREAT）来优化涉及家庭和家庭外配送选项的场景的配送路线和动态定价。该系统旨在通过实时重新优化路线并将客户引导至家庭外配送（当家庭配送成本更高时）来降低成本。通过采用Thompson采样来学习客户偏好，GREAT-ESDD在相似的定价决策时间预算内，与传统的路由求解器相比，利润提高了约11%。 AI

影响这项研究可能导致配送行业更高效的物流和个性化定价策略。

排序理由该集群描述了一篇关于针对特定问题的新AI方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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本文如何被排名

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报道来源 [1]

arXiv cs.AI TIER_1 English(EN) · Attila Lischka (Jeff), Ze Zhou (Jeff), Xuegang (Jeff), Ban, Bal\'azs Kulcs\'ar · 2026-10-15 04:00

GREAT-ESDD：用于有效引导的图边注意力网络以进行交付决策

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…

本文如何被排名

报道来源 [1]

GREAT-ESDD：用于有效引导的图边注意力网络以进行交付决策

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