A real-time synchromodal framework with co-planning for routing of containers and vehicles

卡车 容器(类型理论) 布线(电子设计自动化) 多式联运 计算机科学 服务(商务) 火车 过程(计算) 运输工程 运筹学 车辆路径问题 计算机网络 工程类 业务 汽车工程 机械工程 地图学 营销 地理 操作系统
作者
Rie B. Larsen,Wenjing Guo,Bilge Atasoy
出处
期刊:Transportation Research Part C-emerging Technologies [Elsevier]
卷期号:157: 104412-104412
标识
DOI:10.1016/j.trc.2023.104412
摘要

This paper considers a decentralized container transport system in which two decision-makers are involved in getting a container from its origin to its destination: a logistics service provider (LSP) and a flexible service operator (FSO). While the LSP receives shipment requests from shippers and controls the movement of containers over a multimodal network by booking scheduled (e.g., barges and trains) and flexible services (e.g., trucks) from service operators, the FSO manages a fleet of vehicles (e.g., trucks) that have flexible routes and departure times to fulfill the transport requests proposed by the LSP. In the literature, most of the studies focus on either container routing, by assuming all services have fixed routes and trucks are unlimited, or vehicle routing in a road network. This paper investigates the integrated problems of routing containers and vehicles through a multimodal network from a decentralized perspective considering the decision authorities of the LSP and the FSO. A synchromodal framework is designed to control the decision process which enables to utilize the benefits of real-time mode and route changes. To investigate the impact of communication, we develop a co-planning method under the synchromodal framework to coordinate the transport plans between the LSP and the FSO in real-time. The co-planning method considers a realistic level of information exchange and adheres to no changes in their responsibilities and authorities compared to current practice. The performance of the co-planning method is evaluated under various scenarios. The experimental results show that co-planning, using expected transport request fulfillment as feedback, reduces the total costs of container transportation and decreases the distance traveled by flexible vehicles under most of the scenarios.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
自然的听南完成签到 ,获得积分10
1秒前
不安的可乐完成签到,获得积分10
1秒前
无花果应助chen采纳,获得10
2秒前
micett完成签到,获得积分10
3秒前
liu95完成签到 ,获得积分10
3秒前
子车半烟发布了新的文献求助10
3秒前
科研通AI6应助美晶采纳,获得10
3秒前
lshl2000完成签到,获得积分10
4秒前
波波完成签到 ,获得积分10
4秒前
attilio完成签到,获得积分10
4秒前
4秒前
嗯啊完成签到,获得积分10
4秒前
浮游应助Merlin采纳,获得10
4秒前
awen完成签到,获得积分10
5秒前
11完成签到,获得积分10
5秒前
zz完成签到,获得积分10
5秒前
liuxu完成签到,获得积分10
5秒前
谦让晓晓发布了新的文献求助10
5秒前
tanlaker完成签到,获得积分10
6秒前
着急的千山完成签到 ,获得积分10
7秒前
李某某完成签到,获得积分0
7秒前
7秒前
刘玉欣完成签到 ,获得积分10
8秒前
Sulphide完成签到,获得积分10
8秒前
开心子骞完成签到,获得积分10
8秒前
ronaldo完成签到,获得积分10
9秒前
量子星尘发布了新的文献求助10
9秒前
9秒前
科目二三次郎完成签到,获得积分10
10秒前
10秒前
修辛发布了新的文献求助10
10秒前
LmyHusband发布了新的文献求助10
10秒前
10秒前
张曼玉完成签到,获得积分10
11秒前
简单的百川完成签到,获得积分20
11秒前
111111完成签到,获得积分10
11秒前
12秒前
吃颗电池发布了新的文献求助10
12秒前
科研通AI2S应助王某人采纳,获得10
12秒前
哈哈哈完成签到 ,获得积分10
12秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Encyclopedia of Reproduction Third Edition 3000
Comprehensive Methanol Science Production, Applications, and Emerging Technologies 2000
From Victimization to Aggression 1000
化妆品原料学 1000
小学科学课程与教学 500
Study and Interlaboratory Validation of Simultaneous LC-MS/MS Method for Food Allergens Using Model Processed Foods 500
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5645392
求助须知:如何正确求助?哪些是违规求助? 4768659
关于积分的说明 15028508
捐赠科研通 4803961
什么是DOI,文献DOI怎么找? 2568583
邀请新用户注册赠送积分活动 1525914
关于科研通互助平台的介绍 1485551