Modelling the impact of liner shipping network perturbations on container cargo routing: Southeast Asia to Europe application

Understanding how container routing stands to be impacted by different scenarios of liner shipping network perturbations such as natural disasters or new major infrastructure developments is of key importance for decision-making in the liner shipping industry. The variety of actors and processes within modern supply chains and the complexity of their relationships have previously led to the development of simulation-based models, whose application has been largely compromised by their dependency on extensive and often confidential sets of data. This study proposes the application of optimisation techniques less dependent on complex data sets in order to develop a quantitative framework to assess the impacts of disruptive events on liner shipping networks. We provide a categorization of liner network perturbations, differentiating between systemic and external and formulate a container assignment model that minimises routing costs extending previous implementations to allow feasible solutions when routing capacity is reduced below transport demand. We develop a base case network for the Southeast Asia to Europe liner shipping trade and review of accidents related to port disruptions for two scenarios of seismic and political conflict hazards. Numerical results identify alternative routing paths and costs in the aftermath of port disruptions scenarios and suggest higher vulnerability of intra-regional connectivity

Modelling the impact of liner shipping network perturbations on container cargo routing: Southeast Asia to Europe application

Understanding how container routing stands to be impacted by different scenarios of liner shipping network perturbations such as natural disasters or new major infrastructure developments is of key importance for decision-making in the liner shipping industry. The variety of actors and processes within modern supply chains and the complexity of their relationships have previously led to the development of simulation-based models, whose application has been largely compromised by their dependency on extensive and often confidential sets of data. This study proposes the application of optimisation techniques less dependent on complex data sets in order to develop a quantitative framework to assess the impacts of disruptive events on liner shipping networks. We provide a categorization of liner network perturbations, differentiating between systemic and external and formulate a container assignment model that minimises routing costs extending previous implementations to allow feasible solutions when routing capacity is reduced below transport demand. We develop a base case network for the Southeast Asia to Europe liner shipping trade and review of accidents related to port disruptions for two scenarios of seismic and political conflict hazards. Numerical results identify alternative routing paths and costs in the aftermath of port disruptions scenarios and suggest higher vulnerability of intra-regional connectivity

Sea Container Terminals

Due to a rapid growth in world trade and a huge increase in containerized goods, sea container terminals play a vital role in globe-spanning supply chains. Container terminals should be able to handle large ships, with large call sizes within the shortest time possible, and at competitive rates. In response, terminal operators, shipping liners, and port authorities are investing in new technologies to improve container handling infrastructure and operational efficiency. Container terminals face challenging research problems which have received much attention from the academic community. The focus of this paper is to highlight the recent developments in the container terminals, which can be categorized into three areas: (1) innovative container terminal technologies, (2) new OR directions and models for existing research areas, and (3) emerging areas in container terminal research. By choosing this focus, we complement existing reviews on container terminal operations

Simultaneous optimization of speed and buffer times for robust transportation systems

Transport companies often have a published timetable. To maintain timetable reliability despite delays, companies include buffer times during timetable development, and adjust the traveling speed during timetable execution. We develop an approach that can integrate decisions at different time scales (tactical and operational). We model execution of the timetable as a stochastic dynamic program (SDP). An SDP is a natural framework to model random events causing (additional) delay, propagation of delays, and real-time speed adjustments. However, SDPs alone cannot incorporate the buffer allocation, as buffer allocation requires to choose the same action in different states of the SDP. Our objective is finding the buffer allocation that yields the SDP which has minimal long run average costs. We derive several analytical insights into the model. We prove tha

Multi-agent system with iterative auction mechanism for master bay plan problem in marine logistics

The support of containerization to trade development demands an efficient solution method for the container loading problem in order to reduce shipment and handling time. Hence, the stowage planning of containers is critical to provide speedy delivery of resources from the area of supply to the area of demand. Moreover, information on container terminal activities, structure of ship, and characteristics of containers is distributed among stowage planners. This information imposes constraints, and so the master bay plan problem (MBPP) becomes NP-hard. Therefore, a multi-agent systems (MAS) methodology is designed to effectively communicate the information and solve the MBPP sustainably. In the designed MAS methodology, an information exchange system (IES) is created for stowage planners to bid for ship slots in each experimental iterative combinatorial auction (ICA) market. The winner in the ICA experiments is provided with the ship slots, and the entire bay plan is prepared. Further, the ship-turnaround time is validated using the data obtained from the benchmark problem

Assessing the eco-efficiency benefits of empty container repositioning strategies via dry ports

Trade imbalances and global disturbances generate mismatches in the supply and demand of empty containers (ECs) that elevate the need for empty container repositioning (ECR). This research investigated dry ports as a potential means to minimize EC movements, and thus reduce costs and emissions. We assessed the environmental and economic effects of two ECR strategies via dry ports—street turns and extended free temporary storage—considering different scenarios of collaboration between shipping lines with different levels of container substitution. A multiparadigm simulation combined agent-based and discrete-event modelling to represent flows and estimate kilometers travelled, CO2 emissions, and costs resulting from combinations of ECR strategies and scenarios. Full ownership container substitution combined with extended free temporary storage at the dry port (FTDP) most improved ECR metrics, despite implementation challenges. Our results may be instrumental in increasing shipping lines’ collaboration while reducing environmental impacts in up to 32 % of the inland ECR emissions

A collaborative decision support framework for sustainable cargo composition in container shipping services

This paper proposes a decision support system (DSS) for optimizing cargo composition, and resulting stowage plan, in a containership of a shipping company in collaboration with en-route ports in the service. Due to considerable growth in transportation over years, an increasing number of containers are being handled by containerships, and ports consequently. Trade imbalances between regions and recent disruptions, such as LA/LB/Shanghai port congestion, blocking of Suez canal, drought in Panama canal, typhoons at ports, COVID-19 restrictions and the lack- and then over-supply of empty containers, have resulted in an accumulation of containers in exporting ports around the world. These factors have underscored the urgency of sustainability and circular economy within the shipping industry. The demand for container transportation is higher than the ship capacities in the recent times. In this regard, it is essential for shipping companies to generate a cargo composition plan for each service by selecting and transporting containers with relatively high financial returns, while offering a realistic stowage plan considering ship stability, capacity limitations and port operations. Ultimately, the selected containers should enable a ship stowage plan which keeps the ship seaworthy obeying complex stability considerations and minimizes the vessel stay at the ports, and port carbon emissions consequently, through efficient collaboration with en-route ports. This study provides a bi-level programming based DSS that selects the set of containers to be loaded at each port of service and generates a detailed stowage plan considering revenue, stowage efficiency and quay crane operational considerations. Numerical experiments indicate that the proposed DSS is capable of returning high-quality solutions within reasonable solution times for all ship sizes, cargo contents and shipping routes, supporting the principles of the circular economy in the maritime domain.</jats:p