速递路线规划的k -指针网络

Xu Zheng
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引用次数: 0

摘要

在本研究中,作者打算提供一个合适的快递配送路径的设计,以缩短交货时间。如果路线没有规划好,城市之间的快速班车的交货时间将非常长。本实验研究的主要目的是将K-means与指针网络优化相结合,检验指针网络在快递路线规划中的能力,提高指针网络在TSP挑战下的性能,获得更短的快递路线规划。本文将改进的K-Pointer-Network与常规的指针网络进行了比较。根据模型理论和实验数据可以证明,在很多情况下,数据样本独立聚类可以提高计算性能和规划结果,并且当模型面临大量测试输入时,K-Pointer-Network优于传统的指针网络,并提供了相对较好的快递路线规划。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
K-Pointer-Network for Express Delivery Routes Planning
In this study, the author intends to provide a suitable design for the express distribution path to shorten delivery times. If the route is not well-planned, the delivery time for an express shuttle between cities will be extremely long. The primary purpose of this experimental research is to combine K-means and pointer network optimization to examine the ability of pointer networks in express route planning, improve pointer network performance in the TSP challenge, and obtain a shorter express route planning. The improved K-Pointer-Network is compared to the regular pointer network in this study. According to model theory and experimental data, it can be demonstrated that clustering data samples independently improves computational performance and planning results in many cases, and that when the model is confronted with a large number of test inputs, the K-Pointer-Network outperforms the traditional pointer network and provides relatively good express route planning.
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