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Port throughput analysis is a challenging task, as it consists of intertwined interactions between a variety of cargos and numerous influencing factors. This study aims to propose a quantitative method to facilitate port throughput analysis by identification of important cargos and key macroeconomic variables.

Mutual information is applied to measure the linear and nonlinear correlation among variables. The method gives a unique measure of dependence between two variables by quantifying the amount of information held in one variable through another variable.

This study uses the mutual information to the Port of Isafjordur in Iceland to underpin the port throughput analysis. The results show that marine products are the main export cargo, whereas most imports are fuel oil, industrial materials and marine product. The aggregation of these cargos, handled in the port, meaningfully determines the non-containerized port throughput. The relation between non-containerized export and the national gross domestic product (GDP) is relatively high. However, non-containerized import is mostly related to the world GDP. The non-containerized throughput shows a strong relation to the national GDP. Furthermore, the results reveal that the volume of national export trade is the key influencing macroeconomic variable to the containerized throughput.

Application of the mutual information in port throughput analysis effectively reduces epistemic uncertainty in the identification of important cargos and key influencing macroeconomic variables. Thus, it increases the reliability of the port throughput forecast.

This paper aims to study the implication of the stochastic gross-profit-per-day objective on the ship profitability and the ship capacity and speed.

The paper has used the mathematical model and the solution methodology given by El Noshokaty, 2013, 2014, 2017a, 2017b, and SOS, 2019.

The paper finds that if the ship owner follows the rate concept and the cargo demand forecast, he can improve the profitability of his company and be able to select the proper capacities and speeds for the ships used.

The findings are not only useful for the shipping or other cargo transport companies but also for businesses like gas reservoir development, car assembly lines in the industry, cooperative farming and crop harvesting in agriculture, port cargo handling in trade and road paving in construction.

The contribution of this paper lies in notifying the ship owners of the possible profitability improvement and the consequences of building ships of larger capacities and slower speeds.

This paper analyzes two external costs often associated with port development, cost to fisheries from marine dredge disposal and damages from air pollution, using estimates of development and operation for a proposed (but since cancelled) container port as a case study. For dredge disposal, a bio-economic model was used to assess short- and long-term and indirect (joodweb) damages to fisheries from marine disposal of clean sediments. In the case of air pollution, estimates of annual activity levels and emission coefficients are used to estimate incremental annual emissions of three key pollutants (NOx, HC and CO) for trucks, trains, yard vehicles, and vessels. These estimates allow for phasing in of strict new air pollution regulations. For both external costs, sensitivity analyses are used to reflect uncertainty. Estimates of shadow values in year 2002 dollars amount from $0.094 per cubic yard to $0.169 per cubic yard of clean dredged material for the selected disposal site and from $0.0584 per mile (jor current control standards) to $ 0. 0023 per mile (after phasing in of new regulations) for air pollution from heavy trucks.

The global economy and air transport business have been negatively affected owing to the COVID-19 pandemic outbreak. As countries tighten restrictions on international movements, the growing emphasis on air cargo places pressure on airports to maintain and upgrade their cargo policies, facilities and operations. Hence, ensuring the competitiveness of cargo airports is pivotal for their survival under volatile global demand. This study aims to evaluate the importance of competitiveness factors for cargo airports and identify areas for further improvement.

This study applies the Best-Worst Method (BWM) to assess the cargo airports' competitiveness factors.

The results identified “Transport Capacity” as the most significant competitiveness factor, implying that airport connectivity is crucial in promoting cargo transportation at hub airports. This result was followed by “Airport Operations' and Facilities' Capacity” and “Economic Growth.”. Additionally, the results identified Hong Kong International Airport as the best-performing cargo airport, followed by Aéroport de Paris-Charles de Gaulle and Incheon International Airport, respectively. Furthermore, both selected European airports are the most competitive airports in terms of “Financial Performance” and appear to be aware of the significance of their brand value.

This study forms a reference framework for evaluating cargo airports’ competitive positions, which may help identify airports’ relative strengths and weaknesses. Moreover, this framework can also serve as a tool to facilitate the strategic design of airports that can accommodate air cargo demand flexibly under demand uncertainty.

The purpose of this paper is to resolve three problems in ship routing and scheduling systems. Problem 1 is the anticipation of the future cargo transport demand when the shipping models are stochastic based on this demand. Problem 2 is the capacity of these models in processing large number of ships and cargoes within a reasonable time. Problem 3 is the viability of tramp shipping when it comes to real problems.

A commodity-trade forecasting system is developed, an information technology platform is designed and new shipping elements are added to the models to resolve tramp problems of en-route ship bunkering, low-tide port calls and hold-cleaning cost caused by carrying incompatible cargoes.

More realistic stochastic cargo quantity and freight can now be anticipated, larger number of ships and cargoes are now processed in time and shipping systems are becoming more viable.

More support goes to ship owners to make better shipping decisions.

New norms are established in forecasting, upscaling and viability in ship routing and scheduling systems.

Recently the route connecting the trans-Korean railway and the trans-Siberian railway has become of particular interest for many academics and policy-makers in East Asian countries. The extensive review of previous studies, however, reveals that literature on the subject is lacking solid analytical framework. Most studies are one-sided, focusing on the political aspects of the issue or paying little attention to the economic aspects of the problem.

This study intends to develop an analytical framework through which the most efficient route among four major alternative routes connecting the trans-Korean and trans-Siberian railways can be identified. It attempts to assign priorities to the four alternative routes according to their level of economic efficiency.

This study utilizes a simple cost-benefit analysis in evaluating the four routes. Cost side, transportation time, effectiveness of customs procedures, and gauge difference are selected as the main economic factors. The volume of cargo, industrial production in adjacent regions, access to natural resources, and market size and foreign investment climate are used to evaluate the benefits of the routes.

The study concludes that Route 3, which connects ‘Busan - Seoul (South Korea) –Pyongyang -Sinuiju (North Korea) –Shenyang –Beijing - Erenhot (China) –Ulaanbaatar (Mongolia) –Ulan-Ude - Moscow (Russia)’ is the most efficient route.

This paper presents a generic framework on port logistics development and its interaction with hinterland regions. Although earlier work on the topic (e.g. by Ferrari et al., 2006; Kuipers and Eenhuizen, 2004) offers valuable insights in the subject, it contains limitations in geographical applicability. Ports indeed face dissimilarities in, for instance, locational characteristics (a.o. distance from the sea and nautical accessibility) and hinterland connections. Only when a model for determining seaport-located logistics activities takes into account these issues of dissimilarity among ports, the framework could be applied to a variety of seaport ranges worldwide. In this paper we aim to provide a first version of such a framework. More particularly, by means of a survey conducted in the Port of Busan the shortcomings of traditional approaches are illustrated. We then propose a more encompassing model, which seems to explain fairly well the attractiveness of Busan in terms of logistics activities. This framework explicitly adds port and hinterland characteristics to the list of factors decisive in the choice of the location of logistics activities. Finally, we would like to remark that our research on this topic is still ongoing and results for surveys planned in New York and Antwerp will be reported in a later stage.

Energy groups are cargo owners with large amounts of energy sources (such as coal) to transport. To achieve a satisfactory tradeoff between the reliability requirements of the sea transportation process and the need to control the investment cost, they usually set up a self-owned fleet supplemented by a chartered fleet. This paper aims to investigate the best fleet structure and to evaluate the investment scheme under volatile circumstances in the shipping market.

The authors construct a mathematical model to determine the ratio of the self-owned fleet to the total fleet to minimize fleet operating costs. The volatility of both freight rates and oil prices is taken into consideration. The CPLEX solver is used to empirically analyze real data from an energy group in China, and the ship investment plan is evaluated considering the technical and economic feasibility.

If the ratio of the self-owned fleet to the total fleet is increased to the optimal of 90.40%, the total operating cost is reduced by 33.98%. Thus, the energy group should increase its capacity with a Panamax vessel of approximately 82,000 DWT. Purchasing a 5-year-old secondhand ship and building a new ship both have good investment return indicators.

For cargo owners engaging in transporting bulk cargo domestically in China, the suggested fleet ratio can provide a reference with a universal application scale, given the boundary economic conditions (including the volatility of freight rates and oil prices in the shipping market) in the paper.

This paper aims to introduce a new mixed integer programming formulation and associated heuristic algorithm to solve the Military Nodal Capacity Problem, which is a type of supply chain network design problem that involves determining the amount of capacity expansion required at theater nodes to ensure the on-time delivery of military cargo.

Supply chain network design, mixed integer programs, heuristics and regression are used in this paper.

This work helps analysts at the United States Transportation Command identify what levels of throughput capacities, such as daily processing rates of trucks and railcars, are needed at theater distribution nodes to meet warfighter cargo delivery requirements.

This research assumes all problem data are deterministic, and so it does not capture the variations in cargo requirements, transit times or asset payloads.

This work gives military analysts and decision makers prescriptive details about nodal capacities needed to meet demands. Prior to this work, insights for this type of problem were generated using multiple time-consuming simulations often involving trial-and-error to explore the trade space.

This work merges research of supply chain network design with military theater distribution problems to prescribe the optimal, or near-optimal, throughput capacities at theater nodes. The capacity levels must meet delivery requirements while adhering to constraints on the proportion of cargo transported by mode and the expected payloads for assets.

Mid-stream operation has had a significant role in Hong Kong’s economic development since the 1960s. Prior to the building of container terminals in Hong Kong, cargo was mainly loaded onto and discharged from ocean-going vessels by mid-stream operations and then shipped to Europe and North America. This paper aims to reinforce mid-stream operation is considered a “must” in supporting the substantial growth of maritime industry and strengthening Hong Kong’s role as an entrepôt.

The authors undertake a historical review of the evolution of Hong Kong’s mid-stream operation over the past half-century and investigate the future of mid-stream operation in light of the Hong Kong Special Administrative Region government’s policy of allocating Public Cargo Working Areas through an open auction process. Semi-structured, in-depth interviews are also undertaken in this study.

The emergence of container terminals generated competition for cargo between container terminals and mid-stream operators. In addition, the Hong Kong Special Administrative Region government’s policy of allocating Public Cargo Working Areas to mid-stream operators through an open auction process intensified negative influences on the survival of the mid-stream operation sector.

To date, mid-stream operation has been abandoned nearly everywhere except in Hong Kong. Yet, Hong Kong’s container system has become the most advanced in the world. The authors explain how and why mid-stream operation still plays such a key role in Hong Kong and how to enhance its sustainability. The authors also discuss the academic and managerial implications of their findings.