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This study demonstrates the application of layer model theory to the analysis of synchronous machines. The derivation of the model from Maxwell's equations is briefly described. With the use of steady-state equations and terminal operation information, a methodology is established, and the synchronous machine operation is modelled. Two case examples are then analysed. It is shown that the layer model methodology can be applied to synchronous machines with promising results.

Over the years many shipping lines have established terminal operation companies, with some set up as independent firms. However, port authorities and local governments have not always welc...

As water and land transportation hubs, container terminals are important infrastructures for national economic and social development and participation in global competition and cooperation. With the rapid economic development, the container throughput of China’s ports is increasing year by year. Accurate prediction of container terminal operation can optimize the terminal resource scheduling and improve the operation efficiency. Therefore, in this paper, we design a system to predict the container terminal operations. Some machine learning and deep learning algorithms are used to predict the number of vessels arriving at the port in the future days and the length of time container barges will be at port. Taking Shanghai Yangshan Port phase IV automated terminal as an example, we also perform some experiments, and the results show that our system can provide accurate predictions for the container terminal operations.

In this work, the international and Chinese standards of bulk liquid dangerous goods terminal storage and handling are compared and evaluated. The safety management of ship operation in port and the safety management of terminal operation are selected as the key contrasting indexes of the port operation of bulk liquid dangerous goods. Afterwards, a revised proposal for the safety management of bulk liquid dangerous goods in port is proposed.

In order to comprehensively evaluate the air pollution control status of bulk terminals, the atmospheric environment control measures and effects of Qingdao port Qiangang company in Shandong Province were studied. By means of field survey, monitoring and data analysis, the present situation of atmospheric environment of the research object was analyzed quantitatively, and compared with the national standards. The research results show that the atmospheric environment and main characteristic pollutants at the boundary of the terminal operation area meet the standard requirements under the premise of using spray, cover, windbreak and other management measures during the monitoring period.

As an interface between sea and land, ports are exposed to a wide range of natural hazards such as cyclones, floods and tsunami. At the same time, marine cargoes are growing both in terms of volume and value. Besides their exposure to various hazards during the sea trip, their concentration in ports increases the risk to the cargo itself as well as to the port. The objective of this paper is twofold. First, our study proposes a framework for catastrophe risk analysis of marine cargoes and ports by breaking-down the terminal operation process. This allows a more in-depth analysis by investigating the different parts of that process. Second, the study formulates a State Transition model for the simulation of scenarios. This is an integrated and robust risk model, to analyse exposure of marine cargoes and ports to natural hazards. The port of Laem Chabang is chosen as an example for demonstrating the risk simulation analysis. Findings show that losses can be in the form of both physical loss/damage and interruption loss with extensive cargo accumulation due to port disruptions.

This paper proposes a new modeling and control methodology for allocating materials in a dry bulk terminal with a finite storage capacity. The dynamical process of material storage allocation in the terminal is modeled using a hybrid system perspective that combines both discrete-event and continuous-time dynamics. The stockyard space is partitioned into a number of slots for exchanging incoming and outgoing material flows in the terminal, leading to a so-called mixed logical dynamical (MLD) model with the maximal storage capacity. Based on the MLD model, a model predictive controller is then proposed for maximizing the economic profit in a rolling horizon manner. A number of Monte Carlo simulations have been performed involving a real case study for analyzing the effects of different slot volumes on the economic performance and the computational performance of the controller. Simulations also demonstrate the potential of the proposed methodology. Note to Practitioners —This paper is motivated by the problem of allocating dry bulk materials in the stockyard of a small import terminal. In current approaches for allocating materials, the storage capacity cannot be considered, and this could lower the terminal profit resulting from delaying the vessel in the terminal when a finite storage capacity is considered. This paper suggests a new approach from a hybrid system perspective that captures the dry bulk terminal operation dynamics. In this paper, we mathematically describe the process of allocating materials into different slots in the stockyard using a hybrid dynamical model and propose a model predictive controller to maximize the terminal operation profit. We then show how the slot size influences the economic performance and analyze its associated computations by conducting simulation experiments involving a case study. Simulation experiments also suggest that this approach achieves significantly more economic benefits compared with current approaches. In future research, a large intermodal terminal will be investigated whereby incoming and outgoing materials of different transport modalities need to be coordinated properly.

Effective prediction of ship arrivals should provide the estimated delay or advance of arrival ships with greater accuracy, and improve the performance of container terminal operations. Therefore, taking Gangji (Yining) Container Terminal (GYCT), China, as an example, this paper resorts to data mining approaches to predict ship arrivals and explore the value of such predicted ship arrivals on the container terminal operation. First, this study applies three data mining approaches, including Back-Propagation network (BP), Classification and Regression Tree (CART) and Random Forest (RF), to estimate the delay or advance of ship arrivals using the collected data of ship arrivals. Then the predictive performance of these three approaches is compared and discussed, it is concluded that RF performs better than BP and CART, and ETA month and ship length are the most important determinants of ship arrivals in GYCT terminal. Finally, series simulation experiments are conducted to assess the value of the ship arrivals predicted by RF model on the improvement on daily operation planning of berth allocation and quay crane assignment in the GYCT terminal. And the results show that incorporating the predicted ship arrivals by RF model is beneficial to improve the performance of operation planning of GYCT terminal.

The occurrence of accidents at container ports results in damages and economic losses in the terminal operation. Therefore, it is necessary to accurately predict accidents at container ports. Several machine learning models have been applied to predict accidents at a container port under various time intervals, and the optimal model was selected by comparing the results of different models in terms of their accuracy, precision, recall, and F1 score. The results show that a deep neural network model and gradient boosting model with an interval of 6 h exhibits the highest performance in terms of all the performance metrics. The applied methods can be used in the predicting of accidents at container ports in the future.

Particular care should be given to the evacuation performance of heavily crowed Passenger Terminal Building in a Roll on/Roll off-Passenger terminal (Ro-Pax PTB). However, the uncertainties, embodied in the fire incident, occupant load or passenger distribution make it difficult to identify the worst-case scenario. Therefore, a systematic simulation-based framework is proposed to find out the worst-case scenario and then evaluate the evacuation performance of the Ro-Pax PTB. The framework comprises Simulation Model for Passenger Terminal Operation (SM-PTO model) and Simulation Model for Passenger Evacuation (SM-PE model). The SM-PTO model is built to get the occupant load and passenger distributions by simulating the operation process and passenger movement s in the Ro-Pax PTB. And the SM-PE model simulates the passenger evacuation to determine the evacuation action time under the simulated occupant load and passenger distribution from the SM-PTO model. A Ro-Pax PTB in Dalian, China is taken as an example to testify the applicability of the proposed framework. The results prove that the feasibility and efficiency of the simulation-based framework in deal with the uncertainties, identifying the evacuation bottlenecks and evaluating the evacuation performance of the Ro-Pax PTB. And it also shows the capability of decision support for improving the internal layout and operation management of the Ro-Pax PTB from the viewpoint of the emergency evacuation performance.

Container terminals are the hubs that connect seas and lands in international transportation. In the globalization context of trade, the pursuit of efficient terminal operation is the goal of container terminals, transportation companies, and local governments. As a connecting transportation tool for terminal loading and unloading operations, horizontal transport, and storage operations, the operation of container trucks is optimized on the basis of a coordinated scheduling strategy with terminal working machinery in order to be in line with the concept of high-efficiency operation. Thus, the shortest operating time of ships is taken as the goal, and then the variables of the docking position of the ship and the number of quay crane operations are considered, a model for the three major processes of ship docking is developed, including the docking of ships and the number of quayside operations by arranging storage, transportation, and quay cranes and container trucks in the backyard. Subsequently, an evolutionary algorithm in Excel solver is used for the calculation of the examples, and the effectiveness of stack scheduling in optimizing terminal operation is finally confirmed on the basis of the cooperative scheduling strategy. According to the analysis results, 23.43% of the operation time can be saved under the loading and unloading coordinated container operation.

To optimize the number of quay cranes in container terminals with twin-40-feet and common quay cranes, this paper first proposed an optimization model to minimize the total costs for container terminal operation. Then a queuing model for different berth throughout capacity is employed considering the characteristic of twin-40-feet quay crane operation and the random arrival of ships. And a quasi-birth-and death theory is introduced to obtain the values of system performance indicators. Finally, the proposed optimization model is applied in a container terminal, and the results prove the effectiveness and feasibility of this optimization model, which can provide a good reference for optimizing quay cranes planning.

In this paper, we consider the optimization of loading sequence and rehandling strategy in the terminal operation. We present an optimization strategy to minimize the number of rehandles, and establish a mathematical model to integrate the loading sequence and the rehandling strategy under the parallel operation of multi-quay cranes. Furthermore, we give an improved genetic algorithm to solve the model. We show the efficiency of the optimization strategy and algorithm by comparing them with previous strategies and heuristics.

Almost all applications perform tasks against user data. Sometimes data is obtained from a user, tasks are performed against the data, and the result is returned immediately. More often, data is obtained, and then it is stored within the application for later use, and eventually tasks are performed against it. Applications make use of data structures to store data that can be utilized throughout the lifetime of an application instance. The Java language contains a number of data structures that are known as Collection types, and they can be utilized for this purpose. These data structures implement the java.util.Collection interface, which provides a variety of methods that are useful for adding, removing, and performing tasks against the data that is used with the collection.

Quay crane (QC) scheduling significantly affects the turn-around time of a container vessel, and it plays an important role in container terminal operation. Lee et al. (An approximation algorithm for quay crane scheduling with non-interference constraints in port container terminals, Presented at Tristan VI, Phuket, June 10–15, 2007) present a 2-approximation algorithm for QC scheduling problem with non-interference constraint. In this paper we revisit Lee’s heuristic for the scenario with small number of QCs, and prove that it is 4/3 and 5/3-approximation for the case with two QCs and the case with three QCs respectively.

The analysis of cargo terminals forwarding activity operational planning problems is provided and their main reasons are established; the existing approaches to improvement of operational planning system of transport infrastructure in theoretical researches of the Russian and foreign authors and also the accumulated experience of the advanced enterprises of the industry are considered; the main objectives which can be solved in technological processes of freights handling and forwarding on terminal technology with application of logistic and economic mathematical methods are formulated; specific features of optimization of the operating plan of forwarding activity of the terminal are considered; statement and creation of the terminal operation planning logistic economic-mathematical model is executed, the choice of model optimization criterion in the form of freight handling and long-distance forwarding costs taking into account indicators of the terminal operation planning quality is reasonable

In order to effectively manage and deploy internal tractors in a port container marine terminal, real-time information concerning the location of the tractors is required so that timely scheduling and planning of tractors control and dispatching can be derived. This paper propose a wireless sensor network-based Truck Flow Management System (TFMS) to help tracking the real-time location of internal tractors in a container terminal so as to streamline the management of the terminal operation. Focusing on the real-time localization, the semi-definite programming (SDP) based approaches are employed by introducing the terminal context information, including prior known road constraints and available time-serial data recorded in the network, into the traditional SDP formulation. Experimental results are presented to show that the proposed formulation and treatments to the problem can greatly decrease the estimated errors compared to the traditional formulation.

Located on the Atlantic coast, near the Northern entrance of the Panama Canal, Manzanillo International Terminal (MIT) is one of the largest transshipment terminal in the world and has a total of 7 berths with a combined total length of over 2,000-meter. The addition of a new berth along with other improvements in this facility is expected to boost the container handling capacity of the terminal from 2.4 million twenty-foot equivalent units (TEU) per annum to 4.0 million TEU. This expansion fulfills an important and strategic need of the terminal in meeting the expected demand in container and roll-on-roll-off (RORO) cargo. The final footprint of the expansion comprised of a 400-meter long berth, 6 mooring and breasting dolphins, 60-meter extension of an existing marginal wharf structure, a 600-square meter RORO platform, and improvements to an existing 300-meter wharf. This paper describes the background, planning, design, and construction challenges encountered in implementing this expansion program with emphasis on how the new expansion relates to the existing terminal operation as well as the planned ultimate configuration of the terminal.

Over the past decades, maritime trade experienced significant growth due to globalization and economic development of nations. Maritime transport contributes to the sustainability of the world trade system through its impact on the economic, social, and environmental well-being of nations. Playing a crucial role as trade facilitators, ports and shipping are important parties in the global economic system. Correspondingly to the growth in maritime trade, the port industry encountered tremendous increase in demand with regards to both physical infrastructure investment and cargo handling. Since the birth of con-tainerization, the port industry and cargo handling methods became more standardized and efficient. This development accelerated the expansion of containerized trade.

According to the characteristics of ZPMC automated container terminal operation system, this paper investigates the equipment distribution problem among transportation system, and establishes the scheduling solution of mathematical model for single ship with the shortest total loading/unloading time. Using an improved particle swarm algorithm as the experimental solving method, results show that the proposed model and algorithm are effective and practical.

This paper discusses the quay crane scheduling problem at indented berth, an extension to the current quay crane scheduling problem in the field of container terminal operation. A mixed integer programming model by considering the unique features of the quay crane scheduling problem at indented berth is formulated. For solution, decomposition heuristic framework is developed and enhanced by Tabu search. To evaluate the performance of the proposed heuristic framework, a comprehensive numerical test is carried out and its results show the good quality of the proposed heuristic framework.

The mathematical formalization of operation process for a terminal complex is proposed and a model taking into account characteristics of a freight terminal and all the possible states of a system is developed., Предложена математическая формализация процесса функционирования терминального комплекса и разработана модель, учитывающая особенности работы грузового терминала и все возможные состояния системы., Запропоновано математичну формалізацію процесу функціонування термінального комплексу та розроблено модель, що враховує особливості роботи вантажного терміналу і всі можливі стани системи.

The main object of this research is to select strategic type of business to build an air-logistics cluster by analyzing the effects and mutual relationship among logistics and its related industries in Incheon. First of all, the scope of airport-logistics and its related industries are classified based on previous studies. A theoretical base is then established to build the logistics clusters for the airport-logistics related industries by classifying into the dependent industry and the relevant industry. Secondly, we suggest the categories of business for the cluster in Incheon: Rail-transportation support service, transportation support service, truck terminal operation service, packing service, the aircraft and its part manufacturing industries and structural steel manufacturing industry. This study is founded its contributions from the suggestion of 1) the logistics-related industry classified into dependent and relevant industry to build theoretical foundation for forming the air-logistics industry cluster and 2) particular selection framework for building air-logistics industry cluster in Incheon.

The goods movement via terminals at ports is a complex operation as it involves use of different modes of transport that includes surface and marine. In this paper, we present three simulation models which can be used to understand and evaluate these operations. The macroscopic simulation model simulates the flows in and out of terminals and ports and it is integrated with a microscopic simulation model of the adjacent road network. A terminal cost model receives inputs from these two models to evaluate the cost associated with the processing of containers inside the terminal. The use of the three models is demonstrated by evaluating the impact of terrorist attack scenarios on a container terminal in LA/LB Port complex. © 2009 IFAC. 129 134 Sponsors: IFAC Technical Committee on Transportation Systems TC 7.4 Conference code: 85831 Cited By :2

This paper addresses efficient berth and crane allocation scheduling at a multi-user container terminal. First, we introduce a formulation for the simultaneous berth and crane allocation problem. Next, by employing genetic algorithm we develop a heuristic to find an approximate solution for the problem. The fitness value of a chromosome is obtained by crane transfer scheduling across berths, which is determined by a maximum flow problem-based algorithm based on a berth allocation problem solution defined by the chromosome. The results of numerical experiments show that the proposed heuristic is applicable to solve this difficult but essential terminal operation problem.