A rolling horizon optimisation model for consolidated hump yard operational planning-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

A rolling horizon optimisation model for consolidated hump yard operational planning

Published:2019-05 Issue: Volume:9 Page:3-21
ISSN:2210-9706
Container-title:Journal of Rail Transport Planning & Management
language:en
Short-container-title:Journal of Rail Transport Planning & Management

Author:

Raut Sumit,Sinha Sudhir Kumar,Khadilkar Harshad,Salsingikar Shripad

Publisher

Elsevier BV

Subject

Computer Science Applications,Modeling and Simulation,Management Science and Operations Research,Transportation,Civil and Structural Engineering

Reference25 articles.

1. Network Models in Railroad Planning and Scheduling. INFORMS. Chapter 3;Ahuja,2005

2. Optimal freight train classification using column generation;Bohlin,2012

3. Hump yard track allocation with temporary car storage;Bohlin,2011

4. Track allocation in freight-train classification with mixed tracks;Bohlin,2011

5. Optimization methods for multistage freight train formation;Bohlin;Transport. Sci.,2015

Cited by 14 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. EVALUATION OF THE TECHNOLOGICAL PROCESS OF WAGON PROCESSING AT SHUNTING STATIONS USING THE SIMULATION MODEL;Scientific Journal of Silesian University of Technology. Series Transport;2023-09-01

2. Optimal resource rescheduling in classification yards considering flexible skill patterns;Journal of Rail Transport Planning & Management;2023-06

3. Quantifying the Influence of Volume Variability on Railway Hump Classification Yard Performance with AnyLogic Simulation;Transportation Research Record: Journal of the Transportation Research Board;2023-04-08

4. An optimization integrated approach for simultaneous allocation of railcars and locomotives for train formation based on a pre-designed time schedule;Journal of Rail Transport Planning & Management;2023-03

5. Railcar Itinerary Optimization in Railway Marshalling Yards: A Graph Neural Network Based Deep Reinforcement Learning Method;2023

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