SEARCH FOR A SOLUTION OF THE CAPACITATED VEHICLE ROUTING PROBLEM (CVRP)

M. Golovanenko
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Abstract

This paper focuses on the capacitated vehicle routing problem (CVRP), which is a challenging optimization problem faced by logistics companies. The objective of CVRP is to determine the optimal routing of a fleet of vehicles to deliver goods to a set of customers, subject to various constraints such as vehicle capacity and distance. The optimization of CVRP can lead to significant cost savings for logistics companies, which is why it has received a lot of attention from researchers and practitioners. To solve the CVRP, the author has proposed an interface based on Dash components, which allows users to input information necessary for setting up and solving the problem in the format of Microsoft Excel files. The service accommodates both the coordinates of the logistics network points and the matrix of distances between them as input data. The graphical visualization of the routes determined by the optimization package is also provided, making it easy for users to interpret the results. One of the key features of the service is its ability to automatically construct the distance matrix, which can be a time-consuming and error-prone process when done manually. The input data for the network of logistics points can be presented in the form of coordinates, and the service can estimate distances in two ways - the method of distances of Manhattan blocks and the method of Euclidean distances. This flexibility allows users to choose the most appropriate method for their particular use case. The service is hosted on the Google Cloud Platform, which enables users to access and work with it from energy-efficient mobile devices as well as computers. This is particularly important in the context of the energy crisis caused by the aggressor in Ukraine, where energy efficiency is critical. The service's accessibility from energy-efficient devices makes it a valuable tool for users seeking to optimize their operations in the face of energy constraints.
有能力车辆路径问题的求解
研究了有能力车辆路径问题,这是物流企业面临的一个具有挑战性的优化问题。CVRP的目标是在车辆容量和距离等各种约束条件下,确定车队向一组客户运送货物的最佳路线。CVRP的优化可以为物流公司节省大量成本,这就是为什么它受到了研究人员和从业者的广泛关注。为了解决CVRP问题,作者提出了一种基于Dash组件的界面,允许用户以Microsoft Excel文件的格式输入设置和解决问题所需的信息。该服务将物流网络点的坐标和它们之间的距离矩阵作为输入数据。还提供了由优化包确定的路由的图形化可视化,方便用户解释结果。该服务的一个关键特性是它能够自动构建距离矩阵,如果手工完成,这可能是一个耗时且容易出错的过程。物流点网络的输入数据可以以坐标的形式呈现,服务可以用两种方法估计距离——曼哈顿街区距离法和欧几里得距离法。这种灵活性允许用户为他们的特定用例选择最合适的方法。这项服务托管在谷歌云平台上,用户可以通过节能的移动设备和电脑访问并使用它。在乌克兰侵略者造成能源危机的背景下,这一点尤其重要,因为能源效率是至关重要的。该服务可通过节能设备访问,这使其成为用户在面临能源限制时寻求优化操作的宝贵工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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