论文标题
用于路线计划利用几何信息的约束编程算法
Constraint Programming Algorithms for Route Planning Exploiting Geometrical Information
论文作者
论文摘要
影响人员或商品运输的问题在行业和商业中很丰富，而且似乎也处于更复杂的问题的起源。近年来，物流和运输部门不断受到技术进步支持的支持，即具有竞争力的公司正在诉诸于旨在效率和有效性的创新技术。这就是为什么公司越来越多地使用人工智能（AI），区块链和物联网（IoT）等技术的原因。 特别是人工智能通常用于解决优化问题，以便为用户提供最有效的利用可用资源的方法。在这项工作中，我们概述了我们目前有关基于CLP技术开发的新算法开发的研究活动，用于利用其中许多或其某些变体中本质上存在的几何信息的路线计划问题。到目前为止，这项研究尤其集中在欧几里得旅行销售人员问题（Euclidean TSP），目的是利用将来在同一类别的其他问题（例如Euclidean车辆路由问题（Euclidean VRP））中获得的结果。
Problems affecting the transport of people or goods are plentiful in industry and commerce and they also appear to be at the origin of much more complex problems. In recent years, the logistics and transport sector keeps growing supported by technological progress, i.e. companies to be competitive are resorting to innovative technologies aimed at efficiency and effectiveness. This is why companies are increasingly using technologies such as Artificial Intelligence (AI), Blockchain and Internet of Things (IoT). Artificial intelligence, in particular, is often used to solve optimization problems in order to provide users with the most efficient ways to exploit available resources. In this work we present an overview of our current research activities concerning the development of new algorithms, based on CLP techniques, for route planning problems exploiting the geometric information intrinsically present in many of them or in some of their variants. The research so far has focused in particular on the Euclidean Traveling Salesperson Problem (Euclidean TSP) with the aim to exploit the results obtained also to other problems of the same category, such as the Euclidean Vehicle Routing Problem (Euclidean VRP), in the future.
