From a feeder port to a hub port: the evolution pathways, dynamics and perspectives of Ningbo-Zhoushan port (China)

This paper analyses the spatio-temporal evolution of Ningbo-Zhoushan port growing from a feeder port to a hub port finding the historical pathways followed by its expanding in terms of container throughput capacity and total traffic. The dynamic mechanism of evolution is the results of economic globalization, containerization and its natural endowments in channel and terminal depths. Analysis of the traffic evolution and its underlying dynamics suggest 3 periods in the development processes of container transport in Ningbo-Zhoushan: (1) adoption period (1986–2000) in which the main dynamics is the impact of the Chinese ‘Open Door policy’; (2) acceleration period (2001–2008) in which the dynamics is related of the mainland China's entry into the World Trade Organization; (3) peak growth period (2009-now) in which the dynamics is impacted by the anti-crisis strategy against the financial and economic crisis in 2008. We analyse the perspectives of Ningbo-Zhoushan port. ARIMA model is employed to forecast the container traffic in the coming future; about after 2026, the throughput in Ningbo-Zhoushan port would reach about 49 million TEU which would be approximately equal to that of Shanghai port. The resultant port development would exemplify a model of spatial distribution such as a multi-layered gateway hub. In the respect of growth potential, Ningbo-Zhoushan port possesses excellent coastline resource suitable for deep-water berthing, bonded port policy and free trade zone policy. Geographical position, service level, hinterland economic level and government will support its perspectives.Peer ReviewedPostprint (author's final draft

Estimation of Container Traffic at Seaports by Using Several Soft Computing Methods: A Case of Turkish Seaports

Container traffic forecasting is important for the operations and the design steps of a seaport facility. In this study, performances of the novel soft computing models were compared for the container traffic forecasting of principal Turkish seaports (Istanbul, Izmir, and Mersin seaports) with excessive container traffic. Four forecasting models were implemented based on Artificial Neural Network with Artificial Bee Colony and Levenberg-Marquardt Algorithms (ANN-ABC and ANN-LM), Multiple Nonlinear Regression with Genetic Algorithm (MNR-GA), and Least Square Support Vector Machine (LSSVM). Forecasts were carried out by using the past records of the gross domestic product, exports, and population of the Turkey as indicators of socioeconomic and demographic status. Performances of the forecasting models were evaluated with several performance metrics. Considering the testing period, the LSSVM, ANN-ABC, and ANN-LM models performed better than the MNR-GA model considering overall fitting and prediction performances of the extreme values in the testing data. The LSSVM model was found to be more reliable compared to the ANN models. Forecasting part of the study suggested that container traffic of the seaports will be increased up to 60%, 67%, and 95% at the 2023 for the Izmir, Mersin, and Istanbul seaports considering official growth scenarios of Turkey

Planning and control of autonomous mobile robots for intralogistics: Literature review and research agenda

Autonomous mobile robots (AMR) are currently being introduced in many intralogistics operations, like manufacturing, warehousing, cross-docks, terminals, and hospitals. Their advanced hardware and control software allow autonomous operations in dynamic environments. Compared to an automated guided vehicle (AGV) system in which a central unit takes control of scheduling, routing, and dispatching decisions for all AGVs, AMRs can communicate and negotiate independently with other resources like machines and systems and thus decentralize the decision-making process. Decentralized decision-making allows the system to react dynamically to changes in the system state and environment. These developments have influenced the traditional methods and decision-making processes for planning and control. This study identifies and classifies research related to the planning and control of AMRs in intralogistics. We provide an extended literature review that highlights how AMR technological advances affect planning and control decisions. We contribute to the literature by introducing an AMR planning and control framework t

IRAN'S POTENTIAL AS A LANDBRIDGE FOR FORMER USSR REPUBLICS: A SCENARIO APPROACH

Merged with duplicate record 10026.1/451 on 01.02.2017 by CS (TIS)The concept of a landbridge refers to different types of integrated origin-destination international movements of shipments (in various combinations of sea, land and air) under a single waybill. There are different examples of landbridges with different characteristics related to transport supply facilities, organisational structure and managerial skills. Certain limitations of existing landbridge studies are discussed. They include the failure of a comprehensive academic study to account jointly for both demand and supply of landbridge services. Most articles on landbridges discuss the Trans-Siberian Railway or east-west coast landbridges of the United States of America. No comprehensive academic studies of landbridges in general were found. The main features of the research can be summarised as: *A comprehensive review of literature related to landbridges * An investigation and analysis of Iranian transport supply and demand including both domestic and foreign trade. * An investigation and analysis of the demand of the Central Asian and Caucasus countries (Former USSR republics) for transport * The development of a demand and supply model related to an Iranian Sea-landbridge (ISLB) for eight Central Asian and Caucasus countries and Iran. * Evaluation of the impacts of demand on landbridge supply. *A comprehensive review of the scenario approach and its application to the Iranian Sea landbridge study using a regression technique. Three scenarios are developed (optimistic, most probable and pessimistic). The main result of the scenario modelling suggests that the transport system of Iran requires considerable improvement to compete effectively with other landbridges, given an increase in trade from Iran and the Central Asian and Caucasus countries.the Ministry of the Culture and Higher Education and the University of Sistan and Baluchestan of the Islamic republic of Iran; in collaboration with the Programming and Budgeting Organisation, and Central Bank (Bank Markazi) of the Islamic republic of Ira

Reconfigurable Antenna Systems: Platform implementation and low-power matters

Antennas are a necessary and often critical component of all wireless systems, of which they share the ever-increasing complexity and the challenges of present and emerging trends. 5G, massive low-orbit satellite architectures (e.g. OneWeb), industry 4.0, Internet of Things (IoT), satcom on-the-move, Advanced Driver Assistance Systems (ADAS) and Autonomous Vehicles, all call for highly flexible systems, and antenna reconfigurability is an enabling part of these advances. The terminal segment is particularly crucial in this sense, encompassing both very compact antennas or low-profile antennas, all with various adaptability/reconfigurability requirements. This thesis work has dealt with hardware implementation issues of Radio Frequency (RF) antenna reconfigurability, and in particular with low-power General Purpose Platforms (GPP); the work has encompassed Software Defined Radio (SDR) implementation, as well as embedded low-power platforms (in particular on STM32 Nucleo family of micro-controller). The hardware-software platform work has been complemented with design and fabrication of reconfigurable antennas in standard technology, and the resulting systems tested. The selected antenna technology was antenna array with continuously steerable beam, controlled by voltage-driven phase shifting circuits. Applications included notably Wireless Sensor Network (WSN) deployed in the Italian scientific mission in Antarctica, in a traffic-monitoring case study (EU H2020 project), and into an innovative Global Navigation Satellite Systems (GNSS) antenna concept (patent application submitted). The SDR implementation focused on a low-cost and low-power Software-defined radio open-source platform with IEEE 802.11 a/g/p wireless communication capability. In a second embodiment, the flexibility of the SDR paradigm has been traded off to avoid the power consumption associated to the relevant operating system. Application field of reconfigurable antenna is, however, not limited to a better management of the energy consumption. The analysis has also been extended to satellites positioning application. A novel beamforming method has presented demonstrating improvements in the quality of signals received from satellites. Regarding those who deal with positioning algorithms, this advancement help improving precision on the estimated position

Scientific Workflow Scheduling for Cloud Computing Environments

The scheduling of workflow applications consists of assigning their tasks to computer resources to fulfill a final goal such as minimizing total workflow execution time. For this reason, workflow scheduling plays a crucial role in efficiently running experiments. Workflows often have many discrete tasks and the number of different task distributions possible and consequent time required to evaluate each configuration quickly becomes prohibitively large. A proper solution to the scheduling problem requires the analysis of tasks and resources, production of an accurate environment model and, most importantly, the adaptation of optimization techniques. This study is a major step toward solving the scheduling problem by not only addressing these issues but also optimizing the runtime and reducing monetary cost, two of the most important variables. This study proposes three scheduling algorithms capable of answering key issues to solve the scheduling problem. Firstly, it unveils BaRRS, a scheduling solution that exploits parallelism and optimizes runtime and monetary cost. Secondly, it proposes GA-ETI, a scheduler capable of returning the number of resources that a given workflow requires for execution. Finally, it describes PSO-DS, a scheduler based on particle swarm optimization to efficiently schedule large workflows. To test the algorithms, five well-known benchmarks are selected that represent different scientific applications. The experiments found the novel algorithms solutions substantially improve efficiency, reducing makespan by 11% to 78%. The proposed frameworks open a path for building a complete system that encompasses the capabilities of a workflow manager, scheduler, and a cloud resource broker in order to offer scientists a single tool to run computationally intensive applications