Search

Yard planning is essential for efficient operations in container terminals, especially for ports with limited storage space. To improve the utilisation of space and the efficiency of container handling in a terminal, operators require flexible yard space planning strategies to manage job workloads and yard-to-berth transportation costs. In previous studies, the inter-related decision making process for berths and yards has normally been studied separately, and yard planning models are designed with deterministic inputs of berths, where many existing terminals are operating with sub-optimal efficiency. In this paper, we consider different policies of the scattered stacking strategy for export containers and analyse the entire cycle of container handling from yard block to home berth, where the home berth is a quay section which includes the preferred berthing place of a vessel upon its arrival. We analyse three stacking policies, namely exclusive, cross-area, and buffer-area stacking policies, and formulate the planning problem for yard storage and related home berths into MILP (mixed integer linear programming) models. Solutions are obtained with a two-stage approach method. The numerical analysis demonstrates that the workload imbalance can be significantly reduced by implementing either the cross-area or buffer-area container stacking policy. [ABSTRACT FROM AUTHOR]

Highlights • The economic impacts of the smart port industry on the Korean economy are analyzed. • Four kinds of classification methods are derived using a modified hybrid methodology combining Delphi techniques and input-output (I-O) analysis. • The range of induction coefficients of production, value added, and employment for the smart port industry are quantitatively calculated and compared to those of the port industry. • Additionally, inter-industry linkage effects for the smart port and port industry are examined. Abstract Recently, state-of-the-art technologies such as the Internet of Things and information and communications technology have been applied to the port logistics field in accordance with the advent of the fourth industrial revolution globally. In line with this trend, developed countries are developing and applying smart port technology in the port industry. However, few studies have investigated the economic impact of this activity. Thus, by reviewing the various definitions and policies of the smart port industry and applying a modified hybrid methodology combining Delphi surveys and input-output analysis, this study estimates the economic impact of the smart port industry on the Korean economy with a sophisticated yet reasonable range of values. The smart port industry is dominated by the forward linkage effect, which means the smart port industry is used as an intermediary material or process in other industries. Furthermore, compared with the port industry, the smart port industry has an especially large impact on productivity, value added, and employment. [ABSTRACT FROM AUTHOR]

Many variables are included in planning and management of port terminals. They can be economic, social, environmental and institutional. Agent needs to know relationship between these variables to modify planning conditions. Use of Bayesian Networks allows for classifying, predicting and diagnosing these variables. Bayesian Networks allow for estimating subsequent probability of unknown variables, basing on know variables. In planning level, it means that it is not necessary to know all variables because their relationships are known. Agent can know interesting information about how port variables are connected. It can be interpreted as cause-effect relationship. Bayesian Networks can be used to make optimal decisions by introduction of possible actions and utility of their results. In proposed methodology, a data base has been generated with more than 40 port variables. They have been classified in economic, social, environmental and institutional variables, in the same way that smart port studies in Spanish Port System make. From this data base, a network has been generated using a non-cyclic conducted grafo which allows for knowing port variable relationships - parents-children relationships-. Obtained network exhibits that economic variables are – in cause-effect terms-cause of rest of variable typologies. Economic variables represent parent role in the most of cases. Moreover, when environmental variables are known, obtained network allows for estimating subsequent probability of social variables. It has been concluded that Bayesian Networks allow for modeling uncertainty in a probabilistic way, even when number of variables is high as occurs in planning and management of port terminals. [ABSTRACT FROM AUTHOR]

Zheng, S.; Wang, A.; Mohmand, Y.T., and He, Y., 2017. Path optimum algorithm for container relocation problems in port terminals worldwide. The container relocation problem (CRP) is concerned with emptying a cluster of identical containers stacked in one bay where every container is given a fixed extractive sequence with the fewest number of relocations. Such a typical problem has been examined in this paper. This research differs from previous studies in the following aspects: First, the retrieval paths of the CRP is proposed and its nondeterministic polynomial-time-hardness has been proved. Moreover, a mathematical model is presented that can provide the theoretical basis for the current research. Since the feasible retrieval paths are numerous, heuristic rules are presented to effectively reduce the resolution space. In addition, a new path optimum algorithm (POA) based upon heuristics is proposed to find the optimal solution for any-scale instances in a shorter central processing unit run time. Numerical experiments and comparisons with the other algorithms from the literature show the superiority, high efficiency, robustness, and accuracy of this algorithm. As competition among coastal and inland container ports has become fierce, POA can be used to increase port handling efficiency and facilitate the decision making regarding container port infrastructure planning, and contribute to coastal research worldwide. [ABSTRACT FROM AUTHOR]

Multifarious proposals for siting, design, construction, and operation of onshore and offshore liquefied natural gas (LNG) import terminals in California have recently undergone a rigorous federal and state regulatory appraisal. The regulations call for compliance with various environmental, public safety, and security mandates encoded in legal statutes. Public safety from the hazards of a large-scale LNG spill over water, during LNG tanker transit or marine terminal operation, emerged as the dominant concern for the affected local communities. To address their apprehension, extensive modeling of potentially perilous beyond design basis spill scenarios, ensuing from natural, accidental, and malevolent intentional events was conducted. It entailed finite element modeling for vessel collision with diverse LNG tanker types and applying computational fluid dynamics to predict the extent of LNG spread over water, atmospheric dispersion of vapor cloud, and the consequences of ignition. The objective was to appraise the adverse impacts of cryogenic fluid, fire propagation, and thermal radiation on humans and property not associated with these LNG terminals. Based on insights from risk analyses for three LNG projects in California, challenges in developing complex mathematical models, assessing public safety, and specification of safety criteria are delineated to benefit others planning similar ventures in California or elsewhere. [ABSTRACT FROM AUTHOR]

Many container terminals in the world adopt the consolidated yard planning strategy, where containers to be loaded into the same vessel are stacked in groups. This has been a good strategy because when a vessel is loading, yard cranes will be stationed at these locations, and the trucks shuttle between the quay cranes and the yard cranes almost in a conveyor belt fashion. These locations are optimally chosen such that no two groups of containers are stacked in close vicinity if they are to be loaded simultaneously. However, when there is a change in vessel arrival schedule, it may cause congestion of trucks at yard locations where groups of containers in near vicinity are loading simultaneously. While the Robust Optimisation community may suggest having a robust plan-a plan that is immune to uncertainty, in this paper, we will like to find a solution that allows us to change easily when uncertainty reveals-a plan that is nimble. While the optimum solution for the nimble plan could be intractable, we explore various heuristics that enable us to find good solutions. [ABSTRACT FROM AUTHOR]

We consider a terminal operator who provides container handling services at multiple terminals within the same port. In this setting, the well-known berth allocation problem can no longer be considered for each terminal in isolation since vessel calls should be spread over the various terminals to avoid peaks and troughs in quay crane utilization, and an allocation of two connecting vessels to different terminals will generate inter-terminal container transport. In this paper, we address the problem of spreading a set of cyclically calling vessels over the various terminals and allocating a berthing and departure time to each of them. The objectives are (1) to balance the quay crane workload over the terminals and over time and (2) to minimize the amount of inter-terminal container transport. We develop a solution approach based on mixed-integer programming that allows to solve real-life instances of the problem within satisfactory time. Additionally, a practical case study is presented based on data from the terminal operator PSA Antwerp who operates multiple terminals in the port of Antwerp, Belgium. The computational results show the cost of the currently agreed schedules, and that relatively small modifications can significantly reduce the required crane capacities and inter-terminal transport. [ABSTRACT FROM AUTHOR]

With the rapid development of global ocean transportation, storage space in container terminals is becoming a scarce resource. Hence, the terminal yard only performs as a temporary storage facility for inbound cargos. A storage charge is levied for inbound cargos that stay longer than a free storage time (called free-time-limit). After the free-time-limit, customers may move cargos from the terminal yard to a remote container yard where the storage price is lower than that in the terminal. This paper proposes inbound container storage pricing game models between the container terminal and a remote container yard. Two cases are considered: (1) the inbound container's dwell time is random and follows a probability distribution function; (2) the inbound container's dwell time is sensitive to the storage prices. The primary objective of this paper is to analyze the storage pricing behavior and competition outcomes of the container terminal and the remote container yard. A number of insights and analysis are provided. [ABSTRACT FROM AUTHOR]

In this paper the design of the service network in intermodal barge transport is studied. The network of inland barge terminals is modelled to demonstrate potential cooperations in a corridor network. Cooperation between inland terminals leads to bundling of freight flows in the hinterland of major ports. A service network design model for intermodal barge transport is developed and applied to the hinterland network of the port of Antwerp in Belgium. Selected cooperation schemes are simulated by means of a discrete event simulation model for intermodal barge transport and compared with simulation results of bundling in the port area. Cooperation between inland terminals offers an opportunity to attain economies of scale, but may not be perceived as a sole solution for reducing waiting times of inland barges at sea terminals. A combination of bundling measures in the port area and in the hinterland may be necessary to improve the intermodal transport chain. [ABSTRACT FROM AUTHOR]

Abstract: Truck queuing at marine terminal gates has long been recognized as a source of emissions problem due to the large number of trucks idling. For this reason, there is a great deal of interest among the different stakeholders to lessen the severity of the problem. An approach being experimented by some terminals to reduce truck queuing at the terminal is to provide live views of their gates via webcams. An assumption made by the terminals in this method is that truck dispatchers and drivers will make rational decisions regarding their departure times such that there will be less fluctuations in truck arrivals at the terminal based on the live information. However, it is clear that if dispatchers send trucks to the terminal whenever the truck queues are short and not send trucks when the truck queues are long, it could lead to a perpetual whip lash effect. This study explores the predictive strategies that need to be made by the various dispatchers to achieve the desired effects (i.e. steady arrival of trucks and hence less queuing at the seaport terminal gates). This problem is studied with the use of an agent-based simulation model and the solution to the well known El Farol Bar problem. Results demonstrate that truck depots can manage (without any collaboration with one another) to minimize congestion at seaport terminal gates by using the provided real-time gate congestion information and some simple logics for estimating the expected truck wait time. [Copyright &y& Elsevier]

The paper presents the optimization possibilities of port terminal operations in order to generate maximum gain. Planning these processes is a demanding daily task taken on before dealing with port management, since transhipment operations, cargo loading and dispatching, maintenance and control of transhipment and transportation means are subject to hardy predictable and unexpectable stochastic conditions under which planning optimal terminal operations will include the examination of stochastic processes on the terminal. A model of states and transitions with gain and a model of optimal strategies in terminal management are set up. Furthermore, a model for determining the structure of transhipment equipment is developed. The devised models were adapted to the specificities of a port terminal and tested using the sample of a general cargo terminal. [ABSTRACT FROM AUTHOR]

Generally, an evaluation of container port competitiveness is regarded as a multiple criteria decision-making (MCDM) problem which involves various stakeholders with conflicting interests. To solve MCDM problems, the analytic hierarchy process (AHP) method has been popular, but problems arise in managing uncertainty among decision makers, and contradictory opinions. The key issue discussed in this paper is how to obtain compromise weights (CWs) using a combined AHP procedure. This procedure incorporates Dempster-Shafer theory for eliminating uncertainty in the evaluation, and a levelling process for adjusting the contradictory opinions of each group, a so-called multiple decision-making group problem. For an empirical analysis, container ports located in Northeast Asia, known to exhibit severe port competition, were selected. Using an adoption of the methodology, the matrix of CWs was obtained. Using this matrix permits an exact evaluation of competitiveness in the sampled container ports. [ABSTRACT FROM AUTHOR]

Container stacking rules are an important factor in container terminal efficiency. In this paper, we investigate two concepts to increase efficiency and compare them to several benchmark algorithms, using a discrete-event simulation tool. The first concept is to use knowledge about container departure times, in order to limit the number of reshuffles. We stack containers leaving shortly before each other on top of each other. The second concept is the trade-off between stacking further away in the terminal versus stacking close to the exit points and accepting more reshuffles. It is concluded that even the use of imperfect or imprecise departure time information leads to significant improvements in efficiency. Minimizing the difference in departure times proved to be important. It was also found that the trade-off between stacking further away in the terminal versus stacking close by the exit points and accepting more reshuffles leads to improvements over the benchmark. [ABSTRACT FROM AUTHOR]

The Turkish Straits comprising the Strait of Canakkale, the Strait of Istanbul and the Sea of Marmara are unique in many respects. All dangers and obstacles characteristic of narrow waterways are present and acute in this critical sea lane. This research reveals the simulation of Canakkale (Dardanelle) Strait under different traffic conditions and identifies risky areas. The results of this simulation show that an increase of 25% in the existing traffic grows 43 times in the number of waiting ships (from 1.663 to 73.73), whereas waiting time increases 29 times (from 24.267 to 737.07). As a result of simulations and risk analysis, it is found that Nara turning point is the bottleneck point of the strait due to its topographic structure and the current system. [ABSTRACT FROM AUTHOR]

An introduction is presented in which the editors discuss various reports within the issue on topics including the developments in offshore port service solutions, the berth allocation problem of a terminal operator providing container handling services at several terminals in the same port, and the design of service networks in intermodal barge transport.