An advanced intermodal service network model for a practical transition to synchromodal transport in the US Freight System: A case study

Nasibeh Zanjirani Farahani , James S. Noble , Ronald G. McGarvey , Moein Enayati
{"title":"An advanced intermodal service network model for a practical transition to synchromodal transport in the US Freight System: A case study","authors":"Nasibeh Zanjirani Farahani ,&nbsp;James S. Noble ,&nbsp;Ronald G. McGarvey ,&nbsp;Moein Enayati","doi":"10.1016/j.multra.2022.100051","DOIUrl":null,"url":null,"abstract":"<div><p>Free mode choice, termed “synchromodality,” is an extension of intermodal service network design and is still in the early stages of modeling development. European countries have already started moving toward realizing this innovative transportation system. However, advancement in global transport with longer distances is rare and needs more infrastructural preparation and studies to clarify the steps for such a transition. In this paper, an advanced intermodal service network model (AI-SNM) is proposed to support the development of synchromodal transportation systems. This mixed-integer programming (MIP) model finds the optimal path between O/D pairs while considering horizontal integration of variant transport modes in a supply chain network along with resource constraints and time windows. It minimizes the total transportation cost, transshipment cost, and tardiness with a penalty for delays at intermodal terminals and overdue costs at the destination that accounts for the opening and closing times of the terminals. In order to solve the model for large problem instances, an efficient multiobjective genetic algorithm using a novel coding approach is developed. The algorithm is tested on two US-based case studies, showing the capability of the model to provide cost- and time-saving advantages in long-haul freight. The results of this study can be applied to long-distance global transportation with similar geography and scale.</p></div>","PeriodicalId":100933,"journal":{"name":"Multimodal Transportation","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Multimodal Transportation","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S277258632200051X","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

Free mode choice, termed “synchromodality,” is an extension of intermodal service network design and is still in the early stages of modeling development. European countries have already started moving toward realizing this innovative transportation system. However, advancement in global transport with longer distances is rare and needs more infrastructural preparation and studies to clarify the steps for such a transition. In this paper, an advanced intermodal service network model (AI-SNM) is proposed to support the development of synchromodal transportation systems. This mixed-integer programming (MIP) model finds the optimal path between O/D pairs while considering horizontal integration of variant transport modes in a supply chain network along with resource constraints and time windows. It minimizes the total transportation cost, transshipment cost, and tardiness with a penalty for delays at intermodal terminals and overdue costs at the destination that accounts for the opening and closing times of the terminals. In order to solve the model for large problem instances, an efficient multiobjective genetic algorithm using a novel coding approach is developed. The algorithm is tested on two US-based case studies, showing the capability of the model to provide cost- and time-saving advantages in long-haul freight. The results of this study can be applied to long-distance global transportation with similar geography and scale.

美国货运系统向同步运输过渡的先进多式联运服务网络模型:一个案例研究
自由模式选择,称为“同步模式”,是多式联运服务网络设计的延伸,目前仍处于建模开发的早期阶段。欧洲国家已经开始着手实现这种创新的交通系统。然而,在长途运输方面取得进展是罕见的,需要更多的基础设施准备和研究来阐明这种过渡的步骤。本文提出了一种先进的多式联运服务网络模型(AI-SNM),以支持同步运输系统的发展。该混合整数规划(MIP)模型在考虑供应链网络中各种运输模式的水平集成以及资源约束和时间窗口的同时,找到了O/D对之间的最佳路径。它最大限度地减少了总运输成本、转运成本和延误,并对多式联运码头的延误和目的地的逾期成本进行了处罚,这说明了码头的开启和关闭时间。为了求解大型问题实例的模型,采用一种新的编码方法,开发了一种高效的多目标遗传算法。该算法在两个美国案例研究中进行了测试,表明该模型在长途货运中具有节省成本和时间的优势。该研究结果可应用于地理和规模相似的全球长途运输。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
CiteScore
5.10
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信