大规模路线规划问题中的机器学习方法与应用》特刊简介

IF 4.4 2区工程技术 Q1 OPERATIONS RESEARCH & MANAGEMENT SCIENCE

Transportation Science Pub Date : 2023-12-12 DOI:10.1287/trsc.2023.intro.v58.n1

Matthias Winkenbach, Stefan Spinler, Julian Pachon, Karthik Konduri

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引用次数: 0

摘要

在本文中，我们将介绍 "大规模路由规划问题中的机器学习方法与应用 "特刊，该特刊的灵感来源于学术界对 2021 年亚马逊最后一英里路由研究挑战赛的积极响应。我们将对本特刊收录的论文进行结构化概述，并简要讨论研究挑战赛中其他值得关注的贡献。此外，我们还向读者介绍了本特刊之外由研究挑战赛直接或间接产生的大量同行评审出版物。最后，我们强调了未来将机器学习应用于现实世界路线规划问题研究的一些重要优先事项。

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Introduction to the Special Issue on Machine Learning Methods and Applications in Large-Scale Route Planning Problems

In this paper, we introduce the Special Issue on Machine Learning Methods and Applications in Large-Scale Route Planning Problems, which draws its inspiration from the academic community’s positive reception of the 2021 Amazon Last Mile Routing Research Challenge. We provide a structured overview of the papers featured in this special issue, and briefly discuss other noteworthy contributions to the research challenge. Further, we point the reader to a number of peer-reviewed publications outside of this special issue that directly or indirectly emerged from the research challenge. We conclude by highlighting a number of important priorities for future research into applications of machine learning to real-world route planning problems.

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来源期刊

Transportation Science 工程技术-运筹学与管理科学

CiteScore

8.30

自引率

10.90%

发文量

111

审稿时长

12 months

期刊介绍： Transportation Science, published quarterly by INFORMS, is the flagship journal of the Transportation Science and Logistics Society of INFORMS. As the foremost scientific journal in the cross-disciplinary operational research field of transportation analysis, Transportation Science publishes high-quality original contributions and surveys on phenomena associated with all modes of transportation, present and prospective, including mainly all levels of planning, design, economic, operational, and social aspects. Transportation Science focuses primarily on fundamental theories, coupled with observational and experimental studies of transportation and logistics phenomena and processes, mathematical models, advanced methodologies and novel applications in transportation and logistics systems analysis, planning and design. The journal covers a broad range of topics that include vehicular and human traffic flow theories, models and their application to traffic operations and management, strategic, tactical, and operational planning of transportation and logistics systems; performance analysis methods and system design and optimization; theories and analysis methods for network and spatial activity interaction, equilibrium and dynamics; economics of transportation system supply and evaluation; methodologies for analysis of transportation user behavior and the demand for transportation and logistics services. Transportation Science is international in scope, with editors from nations around the globe. The editorial board reflects the diverse interdisciplinary interests of the transportation science and logistics community, with members that hold primary affiliations in engineering (civil, industrial, and aeronautical), physics, economics, applied mathematics, and business.