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About this book

This book presents new approaches to logistics solutions in global environments, with a special focus on collaborative logistics and intermodality. Contributions in this book are linked to two major initiatives in global logistics - H2020 MSCA-RISE-EU project EC-Asia Research Network on Integration of Global and Local Agri-Food Supply Chains Towards Sustainable Food Security (GOLF), and the ​International Conference on Logistics & Supply Chain (CiLOG). Topics covered in this book are: global logistics environments in manufacturing industries, key logistic decision-making parameters, global logistics management and its impact on container logistics processes, logistic market clusters and many more.

Table of Contents


Challenges and Developments in Integrated Container Supply Chains: A Research Agenda for the Europe-China Research Network on Integrated Container Supply Chains (ENRICH) Project

Since the start of the current century the world has experienced uncertainties in the form of climate change, epidemics, terrorism threats and increasing economic upheaval. These uncertainties create risks for the proper functioning of logistics management and have stimulated research into the development of resilient and sustainable container supply chains (CSCs). The purpose of this study is to examine the research challenges facing the development of resilient and sustainable CSCs and, more specifically, to identify opportunities and provide recommendations for future studies into the operational research, safety, security and resilience, climate change, ICT and intermodal transportation aspects of CSCs. The work will highlight the most difficult research problems in the engineering, operations and management of CSC systems. The proposed research will have a significant impact on our understanding of how the resilience and sustainability of CSC systems can be enhanced through the gathering and exchange of knowledge and expertise in different aspects of CSCs in a newly established consortium funded by the EU (i.e. ENRICH—EC-ChiNa Research Network on Integrated Container Supply Chains, 2013–2017). The success of the research project will provide vital information on how to improve the resilience of CSCs more effectively and how to enhance the sustainability of supply chains in an ever-changing environment where new technologies are developed and introduced. To achieve this objective, this work reviews the major research challenges for, and developments in, integrated CSCs and demonstrates the major uncertainties in CSC operations due to climate change, terrorist threats and increasing economic upheaval. It will also provide insights into the research directions and agenda necessary for tackling these uncertainties in a holistic way at the level of the entire chain, through the use of ICT and intermodal logistics management techniques.
Z. Yang, Y. Wang, D. Li, H. Hjelle, X. Yan, X. Shi, K. Cullinane, D. Zhang, A. Huang, J. Wang, R. Riahi, D. Song, P. Drake, J. E. Hernandez, Z. Jin, L. Shen, Z. Qu, N. Lin

A Research Framework for Cross-National Comparative Logistics

When companies expand internationally under various pressures or opportunities, they find “logistics barriers” in cross-national logistics. This chapter conceptualizes the field of Cross-National Comparative Logistics (CNCL). Firstly, the areas of logistics to compare is discussed which include the concepts, thoughts and practices. Secondly, the factors causing the difference in “logistics” are discussed, which include the development level, market maturation or economic system, and culture. The operationalization of the factors is further discussed.
Wenping Luo

Supply Chain Solutions to Upstream Buyer Consolidation with Green and Resilient Supply Chain Designs in the China-Europe Containerized Cargo Flows

The Asia-Europe container trade is second only to the Transpacific trade in the world in terms of volumes transported. The typical structure of the supply chains associated with this trade is that containers are stuffed in China and the cargo is subsequently cross-docked at a major European logistics hub or closer to the customer for further shipment to the final retailing point. This may be one of the reasons why short sea container shipping has only a limited market share of intra-European cargo flows, since once the cargo is unloaded from containers, it is more likely to be forwarded by land-based modes of transport. Paving the way for a greater proportion of cargo to be cross-docked in China rather than in Europe, may prove to be more cost-efficient and less environmentally damaging than the typical solution. Based on interviews with central actors on the Chinese and European side of the supply chains, this chapter discusses the strengths and weaknesses of the typical solution and alternative solutions such as upstream buyer consolidation. Ultimately, a realization of the potentials related to a shift from the typical design of these supply chains to new alternatives, is dependent on an identification of key decision makers and their gains and losses related to the various solutions. The main decisions related to the design of the supply chains under the alternative solutions seem to be on the European side. Therefore, most shipments of consumer goods from China to Europe seem to be bought with FOB-type of terms. It also seems that European or global LSPs interact with buyers in the design of the supply chains, and that the disadvantages of Chinese LSPs in international logistics network and relations with potential European customers limit their role in this respect. Cost efficiency, lead times, agility and environmental performance of the alternative supply chain design is central to the choice of designs, as is an assessment of potential risks related to the China-Europe container trades. Recent disruptions related to carrier financial robustness has put the issue of building up a resilient supply chains a key issue, which is also relevant in this setting.
Ning Lin, Harald M. Hjelle

Impact Analysis of Slow Steaming on Inland River Container Freight Supply Chain

Based on the literature research and the related concept of inland river container freight supply chain, this chapter analyzes the influence of inland river container freight supply chain under the reduced vessel speeds. Firstly, this chapter describes the research problems and makes assumptions, then establishes a two-echelon inventory management model based on controllable lead time and stable demand, analyzes the impact of slow steaming on inland river container freight supply chain from a quantitative perspective, and finally studies the impact of slow steaming on the inventory cost and inventory strategy of the shipper and consignee in the container freight supply chain, gives some feasibility suggestions.
Wang Zhengguo, Jiang Hui, Xiong Yifan

Modelling Container Port Logistics and Intermodality from the Perspective of Environmental Sustainability

With the protection and restoration of ecological environment becoming the first priority, the chapter constructs Logit model of container port logistics and intermodality from the perspective of environmental sustainability. Then a two-stage game that involves three major container port logistics and intermodality between Port of Shanghai and its hinterland of Yangtze River Economic Belt is analyzed. The Nash equilibria of container port logistics and intermodality are solved taking noise pollution and harmful gas emission into account respectively and simultaneously, which can be decision-making support of regulations promulgated and operation optimized in order to realize environmental sustainability of container port logistics and intermodality.
Gang Dong

Random Forest Regression Model Application for Prediction of China’s Railway Freight Volume

Purpose: The China Railway has an important impact on the transport of domestic energy products. The Chinese Prime Minister sees railway freight as a barometer of the Chinese economy; therefore, the study of China’s Railway freight is meaningful. During the past 5 years, from 2012 to 2016, China Railway freight volume continually declined, leading to a very serious situation. It is important to predict the volume of rail freight because it indicates the development of the Chinese economy. The prediction of China’s railway freight by a traditional regression model is not very effective because it is too sensitive to changes in statistical data. In particular, economic changes in China are now too large, resulting in significant changes in railway freight volume. In this chapter, we aim to use an machine learning model to predict China’s railway freight volume and attempt to determine whether the random forest regression model is more effective than the conventional forecasting method.
Design/methodology/approach: In this chapter, random forest regression is applied to quantitatively predict railway freight volume. Six independent variables were collected from Jan 2001 to Dec 2016 in relation to China’s railway freight. After data analysis, a random forest regression model of China’s railway freight volume was built using the R language. To obtain the most suitable regression model, the random forest regression error is contrasted with the multiple linear regression model. The result shows that random forest regression model performed better than linear regression.
Findings: The results in this study indicate the following: (1) the random forest regression model is able to predict railway freight volume using the selected variables. (2) By comparison of the variance and the normalized mean square error (NMSE) of different models, the best random forest regression model is obtained, and this model performs accurate prediction. (3) Compared with the multiple linear regression model, the random forest regression model exhibits superiority in prediction accuracy, robustness and fitness. (4) Although coal makes up the largest proportion of railway freight, refined oil production also has a large impact.
Yang Wang, Xiaochun Lu

An Optimization Approach for the Train Load Planning Problem in Seaport Container Terminals

In this work an optimization approach for defining loading plans for trains in seaport container terminals is presented. The problem consists in defining the assignment of containers of different length, weight and value to wagon slots of a train, in order to maximize the total value loaded on the train and to minimize unproductive movements, both in the stacking area and of the crane during the loading process. Due to the difficulty in solving this problem for real scenarios, a MIP heuristic solution approach based on a randomized matheuristics is proposed. Computational results are presented and discussed, showing the effectiveness of the proposed heuristic solution method.
Daniela Ambrosino, Davide Anghinolfi, Massimo Paolucci, Silvia Siri

Utilizing Breakthrough Innovations: The Need for Information Sharing as a New Key Performance Indicator for Container Port Operations

As a response to higher customer demand and increased competition, innovations in port operations is of concern for port customers and port operators. The growth in world trade is doubling every 5–7 years with a corresponding increase in cargo container movements, most of which are handled by seaports. Moving more traffic through the limited area of a seaport can only be achieved by an increase in port performance. Shipowners, terminal operators and forwarding agents each have optimized their performance guided by values collected on key performance indicators. The purpose of this chapter is to contribute to the understanding of the use of key performance indicators as a mean to drive port innovations. We argue that the use of standard key performance indicators leaves ports in the region of incremental innovations with a diminishing rate of return of investments, missing out on the potential efficiency growth by breakthrough innovations. Our results from a case study at Oslo port shows that operations suffer from a lack of information sharing resulting in an unused potential, not captured by the current performance indicators. We propose a new Information Sharing Indicator to motivate and guide ports in adopting breakthrough innovations for information sharing.
Bjorn Jager, Ning Lin

Scheduling Periodical Deliveries from a Distribution Centre to Minimize the Fleet Size

This chapter studies the delivery problem in which a distribution center delivers goods to customers periodically. Each customer has a specified delivery frequency. The deliveries to the same customer must be spaced over time as evenly as possible. The objective is to minimize the fleet size. We start from the special version with customers requiring the same delivery frequency, and propose a routing-then-scheduling approach: a routing problem for making one delivery to every customer is first solved and the resulting routes are then scheduled over the period. The study mainly focuses on the scheduling of the routes. Feasibility and optimality of the solution are analyzed. Based on the analysis, we develop a general integer programming model and a two-stage method for the problem with different delivery frequencies. Numerical experiments show that both methods solve the problem quickly. However, the delivery patterns generated by the two-stage models are more stable.
Jiyin Liu, Aiying Rong
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