基于神经网络和神经神经网络的传染病递送策略

Hao Yin, Chenxu Zhang, Jie Yin, Canrong Zhang
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引用次数: 0

摘要

在新冠肺炎疫情持续蔓延的背景下,生鲜外卖平台需要就如何将疫情因素纳入配送策略做出决策。本文针对预约式生鲜配送中配送人员活动范围大、路径长、效率低、风险高的因素,结合配送平台的视角,构建了配送人员的路径规划模型。我们将ALNS算法应用于该模型,并与其他经典的启发式算法进行了比较。结果表明,该模型能够有效降低风险,提高配送效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Delivery strategy under epidemic based on neural network and ALNS
Under the background of the continuous spread of covid-19, fresh food delivery platforms need to make decisions on how to incorporate epidemic factors into their delivery strategies. In this paper, considering the factors of large activity range, long path, low efficiency and high risk of delivery staff in reservation-type fresh food delivery, combined with the perspective of delivery platform, a path planning model is constructed. we apply the ALNS algorithm to the proposed model and compares it with other classical heuristic algorithms. The results show that our proposed model can effectively reduce risks and improve delivery efficiency.
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