Search

Global maritime supply chain (MSC) faces increasing risks of uncertainty in the post COVID-19 era, ports disruptions and congestion are becoming common. To ensure high reliability of container shipping network, this paper study on the issue of locating hub ports and allocating non-hub ports (spokes) to hubs, meanwhile backup hub ports. An extended container shipping hub-and-spoke network design problem (HSN) is investigated, considering the failure and congestion of hubs, a 0–1 nonlinear programming model is developed for minimizing the transportation cost. Furthermore, we simulate container shipping network using Asia-Europe trade data, and propose the approach of particle swarm optimization (PSO) to solve the model. The experimental results show that path replacement cost and congestion cost affect the network design to a great extent, and backup hub ports could improve the reliability of global container shipping networks for capacity scheduling and allocation. This study can provide certain useful managerial insights for the liner company's daily operation, and design flexible container shipping HSN to ensure maximum efficiency after the COVID-19 irruption. [ABSTRACT FROM AUTHOR]

Abstract: This paper addresses the design of container liner shipping networks taking into consideration container management issues including empty container repositioning. We examine two typical service networks with different ship sizes: multi-port calling by conventional ship size and hub-and-spoke by mega-ship. The entire solution process is performed in two phases: the service network design and container distribution. A wide variety of numerical experiments are conducted for the Asia–Europe and Asia–North America trade lanes. In most scenarios the multi-port calling is superior in terms of total cost, while the hub-and-spoke is more advantageous in the European trade for a costly shipping company. [Copyright &y& Elsevier]

The quality of the container ocean shipping network design directly affects the revenue of liner companies. In this paper, a container ocean shipping network design problem (COND) is investigated. Considering that the governments of many countries have proposed carbon-neutral initiatives, coupled with the constant fluctuations in the shipping market, the carbon tax and cargo owners' choice inertia factors are taken into consideration simultaneously. To model the COND, a bi-level programming model is developed to jointly optimize the liner type, calling sequence, calling frequency, and sailing speed. The upper model aims to choose the network design scheme that maximizes the liner company's revenue. The lower model optimizes the freight scheme of the liner company to evaluate the network design scheme selected by the upper model. To solve the abovementioned model, a genetic algorithm is designed, and a real-world trade shipping route between Asia and Western Europe is introduced to perform numerical experiments. Sensitivity analyses are conducted for different carbon tax rates and transportation demands. The experimental results show that the abovementioned model and algorithm can effectively address the COND and provide certain useful managerial insights for the liner company's daily operation. [Display omitted] • A liner shipping network design problem is investigated. • The carbon tax and choice inertia of cargo owners are jointly considered. • A bi-level programming model is established. • A genetic algorithm is designed to solve the abovementioned model. • The conclusions provide guidance to liner companies' daily operations. [ABSTRACT FROM AUTHOR]