Cascading economic losses from port disruptions under capacity constrained multimodal freight networks

Port disruptions due to natural disasters: Insights into port and logistics resilience

Seaport operations are highly important for industries as they rely heavily on imports and exports. A necessary consideration of the port risks is essential to govern the normal running of the seaborne transportation and thus the industrial economies. Trade facilitators, such as ports, will disrupt the smooth flow of supply chains for the industries when a breakdown occurs. The estimation of the economic loss in the industry associated with the port disruption is a challenging task as the relationship between the port and industry clusters is complex. This study aims to examine the existing tools which are in place for the purpose of estimating the risks to industry clusters due to port disruptions. Based on the major limitations of these tools, the study also aims to develop an original approach to address the limitations. This study develops a statistical approach with an integrated Petri Net analysis for the risk assessment in Shenzhen. Recommendations for risk management will be drawn accordingly.

Regional economic losses of China's coastline due to typhoon-induced port disruptions

Estimating economic losses of industry clusters due to port disruptions

Economic impact of typhoon-induced wind disasters on port operations: A case study of ports in China

Currently, long‐distance freight transport is shifting towards multimodal transport, the combination of multiple freight transport modes. Multimodal transport enables enterprises with the same logistics function to operate on the same level of the supply chain. Through horizontal cooperation, these enterprises can give play to their advantages, make up their deficiencies, improve service levels, reduce cost input, and thereby enhance market status. Therefore, multimodal transport is an intensive development model that promotes the alliance between giants. The reasonable path design and planning (PDP) and investment and construction mode (ICM) of the multimodal transport network help freight demanders, as well as multimodal freight transport platforms, obtain the maximum profit. Therefore, this paper explores the PDP and ICM of the multimodal transport network based on big data analysis. Firstly, the influencing factors and behavioral features of multimodal transport were deeply examined, drawing on the logit model and the big data on multiple freight services, namely, railway transport, highway transport, waterway transport, and airway transport. After classifying the freights, the authors analyzed the modeling and decision‐making of path design and optimization (PDO) for multimodal transport network. The proposed model was proved effective through experiments. This paper theoretically explores the goals, principles, and needs of path selection in the modern transportation industry. In a realistic sense, the research findings help decision‐makers optimize their decisions on the multimodal transport network and operate the network at the minimum transport cost.

This paper develops a dynamic freight network simulation–assignment platform for the analysis of multiproduct intermodal freight transportation systems. At the core of the platform is a model framework for the mode–path assignment problem in multimodal freight transportation networks. The framework consists of three main components: a multimodal freight network simulation component, a multimodal freight assignment component, and a multiple product intermodal shortest path procedure. The freight network simulation component incorporates a bulk queuing model to evaluate transfer delay experienced by shipments at intermodal transfer terminals, classification yards, and ports. The multimodal freight assignment component determines the network flow pattern from a mode–path alternative set calculated by the multiple product intermodal shortest path procedure, based on the link travel costs and node transfer delays from the multimodal freight network simulation component. This model can represent individual shipment mode–path choice behavior, consolidation policy, conveyance link moving, and individual shipment terminal transfer in an iterative solution framework.

Optimizing the performance of multimodal freight transport networks involves adequately balancing the interplay between costs, volumes, times of departure and arrival, and times of travel. In order to study this interplay, we propose an assignment model that is able to efficiently determine flows and costs in a multimodal network. The model is based on a so-called user equilibrium principle, which is at the basis of Dynamic Traffic Assignment problems. This principle takes into account transport demands to be shipped using vehicles that transport single freight units (such as trucks) or multiple freight units (such as trains and barges, where demand should be bundled to reach efficient operations). Given a particular demand, the proposed model provides an assignment of the demand over the available modes of transport. The outcome of the model, i.e., the equilibrium point, minimizes users’ generalized costs, expressed as a function of mode, travel time and related congestion, and waiting time for bundling sufficient demand in order to fill a vehicle. The model deals with these issues across a doubly-dynamic time scale and in an integrated manner. One dynamic involves a learning dynamic converging towards an equilibrium (day-to-day) situation, reflecting the reaction of the players towards the action of the others. Another dynamic considers the possible departure time that results in minimum expected costs, also due to the fact that players mutually influence each other on the choice of departure times, due to congestion effects and costs for early/late arrival of freight units. This is a choice within a given time horizon such as a day or a week. We present a study on the influence and sensitivity of different model parameters, in order to analyse the implications on strategic decisions, fostering a target modal share for freight transportation. We also study under which conditions the different modes can be substitutes for each other.

In 2021, economic losses due to supply chain disruptions in the Eurozone amounted to €112.7 billion Euro: Natural catastrophes (e.g., hurricanes, earthquakes, floods, and wildfires) multiply in the wake of climate change. The risks of pandemics, trade restrictions, cyber-attacks, and geopolitical conflicts are omnipresent. Hence, the threat of disruptive events to the European transport network grows ever greater. Additionally, GHG emissions can drastically increase by up to 50% if disruptions are not treated efficiently. Here, the project “Resilient multimodal freight transport network” (ReMuNet) comes into play: ReMuNet will enable the multimodal freight network to react and respond 20% more quickly to disruptive events and help to reduce European inland transport emissions on the main run by over 50% by 2026. As a trailblazer for the Physical Internet, the project pursues the vision to enable and incentivize synchro-modal relay-transport on European rail, road, and inland waterways to increase holistic network resilience. ReMuNet can identify and signal disruptive events and assess their impact on multimodal transport corridors. It reacts quickly to disruptive events in real time. It supports TMS providers to improve route planning resilience by communicating alternative, pre-defined, multimodal transport routes. ReMuNet orchestrates route utilization, suggests transshipment points, and optimizes capacity allocation, minimizing damage and shortening the recovery time. This paper introduces ReMuNet and its vision, objectives, and expected results.

Resilience evaluation and improvement of post-disaster multimodal transportation networks

At the strategic level, multimodal freight network design problems are limited in that they reflect the costs and constraints associated with emissions. The network design problem (NDP) addressed in this study determines investment alternatives for minimizing total system cost, including costs related to greenhouse gas (GHG) emissions, while satisfying the emissions constraint. The NDP can accommodate improvement alternatives in transfer terminals as well as in road and railroad links. In this study, mode-specific travel time functions were used to represent the differences between the modes explicitly, even for the transfer facility. Emission factors were calculated by link travel speed and level of facilities. The empirical application to a container freight network from the Port of Pusan in southeastern South Korea showed the optimal investment strategy for meeting emissions reduction policy objectives. The conclusion is that investment should concentrate on railroad and terminal facilities to induce modal shift. In contrast, investment in congested roads might be a better option for corridors in which the level of railroad service is low and short-distance freight demands are dominant. These results indicate that the proposed network design problem can provide the appropriate investment strategy for reducing GHG emissions and therefore can be a useful approach with regard to GHG emissions reduction policy.

Cascading failure in multimodal transport network may cause huge economic loss and social impact, which has gradually attracted public attention. In view of the coupling effect of nodes in multimodal transport network and the higher complexity of cascading failure process, the concepts of node correlation degree and node cooperation degree are proposed to characterize the characteristics of the network, and a logit model is introduced to calculate the initial load of nodes. In the case of ignoring network interruption, we propose two load redistribution methods: local allocation and global-local allocation. Taking the multimodal transport network in Sichuan–Tibet region of China as an example, the cascading failure effect of multimodal transport network in Sichuan–Tibet region is quantified by sensitivity analysis. The results show that when the load of the multimodal transport network in Sichuan–Tibet region exceeds the maximum capacity but does not exceed 150%∼170% of the network capacity, the network can still operate normally. In addition, the nodes in the multimodal transport network should have 0.3∼0.5 scalable space. In the cascading failure control method, load redistribution based on global-local allocation can minimize the impact of node overload.

Multi-Modal freight models are traditionally built following the well known four steps model in which generation, distribution, modal-split and assignment are seen as separated modules. An alternative approach is to represent the multi-modal network by means of a mono-modal one, in which each particular transport operation (loading or unloading operation, transhipments ...) is represented by a dedicated virtual link. This approach, promoted by several authors, often referenced to as super or virtual is proven to give interesting results, but has some kind of hidden trap, linked to transport distances, that will be presented in this paper and that can only be solved using appropriate assignment techniques. All the traffic between a given pair of origin and destination may not be charged on the same transport mode and/or route. This paper outlines a new usable multi-flow/multi-modal assignment technique that can be applied on large (virtual) freight transportation networks and that solves the distance trap and shows its implementation on the trans-European multimodal freight network. For the covering abstract see ITRD E135582

The paper presents a detailed comparative review of price/cost elasticity estimates published in a number of studies on multi-mode freight transport demands. It attempts to determine which factors could explain the wide diversity of estimates: data aggregation, diversity of markets, and methodology. It also presents new estimates for rail, road, and waterway modes, derived from a multimodal freight network model of the Rhine area market. Direct and cross-elasticities are estimated for 11 groups of commodities and per distance category. The results are critically assessed by comparison with the reviewed studies. The paper concludes with a few recommendations about meaningful uses of existing estimates and the need for additional experiments with different methodologies applied on a common data basis.

Hub seaport multimodal freight transport network design: Perspective of regional integration development