Easy Cases of Deadlock Detection in Train Scheduling

Author:

Dal Sasso Veronica1ORCID,Lamorgese Leonardo1,Mannino Carlo23ORCID,Tancredi Antonio1,Ventura Paolo4ORCID

Affiliation:

1. OptRail, Rome 00154, Italy;

2. SINTEF, Oslo 0373, Norway;

3. University of Oslo, Oslo, Norway;

4. Institute of System Analysis and Informatics (IASI) of CNR, Rome 00185, Italy

Abstract

In a railway network, a deadlock occurs when two or more trains are preventing each other from moving forward by each occupying the tracks required by the other. Deadlocks are rare but pernicious events in railroad operations, and, in most cases, they are caused by human errors and involve only two extra-long trains missing their last potential meet location. In “Easy Cases of Deadlock Detection in Train Scheduling,” V. Dal Sasso, L. Lamorgese C. Mannino, A. Tancredi, and P. Ventura prove that the identification of two-train deadlocks can be performed in polynomial time. Moreover, they also present a pseudo-polynomial but efficient oracle that allows real-time early detection and prevention of any (potential) two-train deadlock in the Union Pacific (a U.S. class 1 rail company) railroad network. A deadlock prevention module based on the work in this paper will be put in place at Union Pacific to prevent all deadlocks of this kind.

Publisher

Institute for Operations Research and the Management Sciences (INFORMS)

Subject

Management Science and Operations Research,Computer Science Applications

Reference23 articles.

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Solving train scheduling problems as a job shop: A brief review;Annals of Mathematics and Physics;2022-11-15

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3