Article
Management
Stefano Fazi, Sourabh Kumar Choudhary, Jing-Xin Dong
Summary: We study a typical daily drayage problem concerning the last-mile logistics at seaports for inland container supply chains. A set of trucks available at an inland container terminal must fulfil shippers' requests of transporting containers within time windows and, to do so, can perform multiple daily trips. The minimization of routing costs also entails synchronizing trucks' trips that retrieve and add empty containers to the inland terminal stock to avoid unnecessary visits to the empty depot.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Computer Science, Artificial Intelligence
Qian Wang, Jianfeng Zheng, Bo Lu
Summary: Considering the influence of economies of scale and ship capacity on empty container repositioning, this paper studies the liner shipping hub location problem with empty container repositioning (LSHLPECR) and the container leasing pricing problem (CLPP). By formulating a mixed integer linear program (MILP) and utilizing the inverse optimization technique, the effectiveness of the studied problems is verified through numerical experiments.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Transportation Science & Technology
Karmel S. Shehadeh, Hai Wang, Peter Zhang
Summary: The last-mile problem refers to providing travel service from the nearest public transportation node to home or other destination. Newly emerged Last-Mile Transportation Systems (LMTS) offer on-demand shared transportation services to address this issue. This paper investigates fleet sizing and allocation for on-demand LMTS, proposing both a stochastic programming model and a distributionally robust optimization model to tackle demand uncertainty challenges.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2021)
Article
Computer Science, Artificial Intelligence
Minyi Cai, Haodong Li, Zhanqing Guo, Shuisheng Lu
Summary: The Chinese rail network is increasing the number of containers to promote intermodal transport service and attract more freight demand. However, the repositioning of empty containers poses a significant challenge due to the spatial imbalance between supply and demand. This article proposes a data-driven framework that uses machine-learning algorithms to forecast empty container supply/demand and develop optimization models for the optimal repositioning plan. The proposed solution method yields optimal plans that may increase total container-kilometer but are more practicable and executable.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2023)
Review
Green & Sustainable Science & Technology
Alaa Abdelshafie, May Salah, Tomaz Kramberger, Dejan Dragan
Summary: This article focuses on the problem of empty-container repositioning and provides a comprehensive evaluation of the commonly used methods, models, and applications. It presents various practices including organizational policies, technical solutions, and modeling applications. Through systematic review, future research opportunities have been identified.
Article
Transportation Science & Technology
Ramon Auad-Perez, Pascal Van Hentenryck
Summary: This paper discusses the design of On-Demand Multimodal Transit Systems (ODMTS) and introduces novel algorithms, including ridesharing in shuttle rides, based on Mixed-Integer Programs (MIP) to determine fleet size optimization. The research demonstrates the potential of ridesharing for reducing costs and transit times in ODMTS designs.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2022)
Article
Green & Sustainable Science & Technology
Wennan Song, Di Liu, Wenyu Rong
Summary: The study aims to optimize railway container transportation in order to improve efficiency and maximize revenue for railway enterprises. By establishing a mixed-integer linear programming optimization model, the study considers the transportation requirements of empty and heavy containers, as well as constraints such as train stops and container reloading. Experimental results show that, with a minimum average loading rate of 70%, 47 lines need to be run, which is 163 less than the candidate lines.
Article
Computer Science, Interdisciplinary Applications
Tian Luo, Daofang Chang, Zhenyu Xu
Summary: This study examines the issue of empty container ordering, analyzing the optimal option ordering level under different circumstances and the impact of option trading price on system profit. The results show that option trading can share risks among forwarders, while the two-part tariff contract can achieve win-win outcomes for the two forwarders.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Computer Science, Artificial Intelligence
S. Rajeswari, C. Sugapriya, D. Nagarajan
Summary: This study focuses on the inventory model of returnable containers for NVOCC with price dependent demand under a fuzzy environment, using ECR and leasing options to replace deficit containers and prevent shortages while minimizing costs. Sensitivity analysis is performed to analyze the impact of fuzziness of several factors on the expected total cost.
COMPLEX & INTELLIGENT SYSTEMS
(2021)
Article
Business
Chao Huang, Ruiyou Zhang
Summary: This article focuses on a novel container drayage transportation problem involving foldable and standard containers. The objective is to minimize the total working time of trucks in operation. An improved truck-state transition method and a mathematical model are designed to describe the problem, and a large neighborhood search algorithm is used to solve it. Experimental results show the effectiveness of the algorithm, and increasing the maximum number of empty foldable containers carried by trucks at a time reduces the total working time of trucks in operation.
IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT
(2023)
Article
Computer Science, Interdisciplinary Applications
Tian Luo, Daofang Chang, Zhenyu Xu, Xiaoyuan Hu
Summary: In this paper, the authors investigate the problem of empty container leasing decision and coordination in the dual-channel container transportation service chain (DCCTSC) under stochastic demand and financial constraints of the carrier. They propose an advance payment financing mode to solve the capital constraint problem and analyze the optimal leasing strategies under decentralized and centralized modes. A joint contract with advance payment financing parameters is designed to coordinate the DCCTSC and the conditions for contract enforceability are discussed. The study shows that the joint contract effectively coordinates the DCCTSC and can increase total system profit by up to 5.23%.
COMPUTERS & INDUSTRIAL ENGINEERING
(2023)
Article
Green & Sustainable Science & Technology
Zirui Liang, Ryuichi Shibasaki, Yuji Hoshino
Summary: This study compared the total management costs of container repositioning of shipping companies using standard and foldable containers through a mathematical model, and found that introducing foldable containers can reduce costs, but over-introduction may increase costs. Increasing the number of containerships can further reduce costs when future demand increases.
Article
Computer Science, Information Systems
Dongyang Zhan, Kai Tan, Lin Ye, Haining Yu, Hao Liu
Summary: This paper proposes a secure external monitoring approach to monitor target containers in another management container, providing a secure monitoring environment. By isolating processes and files one-way, transparent external management containers are implemented to be more secure and suitable compared to existing host-based monitoring approaches in the cloud environment.
CMC-COMPUTERS MATERIALS & CONTINUA
(2021)
Article
Engineering, Marine
De-Chang Li, Hua-Long Yang
Summary: This paper focuses on the container ship routing problem in inland waterway liner transportation. The objective is to design the container ship route and determine the amount of foldable and standard empty containers to be shipped between each port pair to maximize profit. Two mixed integer programming models are established to optimize ship route and shipping strategies, and the models are further improved for higher computational efficiency. Numerical experiments on the Yangtze River are conducted to test the methods, and reference recommendations are provided.
Article
Engineering, Civil
Boting Qu, Linran Mao, Zhenzhou Xu, Jun Feng, Xin Wang
Summary: The study proposed a minimum fleet sizing method called Fleet Sizing for demand-aware Dynamic Ridesharing (FSDR) to accurately determine the fleet size for ridesharing enabled SAV system. By predicting travel demands, measuring demand utility, and maximizing demand utility, the study effectively reduced the vehicle fleet size.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Economics
Akio Imai, Koichi Shintani, Stratos Papadimitriou
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
(2009)
Article
Economics
Koichi Shintani, Rob Konings, Akio Imai
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
(2010)
Article
Transportation
Koichi Shintani, Rob Konings, Etsuko Nishimura, Akio Imai
MARITIME ECONOMICS & LOGISTICS
(2020)
Article
Transportation
Koichi Shintani, Rob Konings, Akio Imai
MARITIME ECONOMICS & LOGISTICS
(2012)
Article
Economics
Koichi Shintani, Akio Imai, Etsuko Nishimura, Stratos Papadimitriou
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
(2007)
