Wyniki wyszukiwania - Biblioteka Nauki

1

Leveraging artificial intelligence to enhance port operation efficiency

100%

Dinh G. H. , Pham H. T. , Nguyen L. C. , Dang H. Q. , Pham N. D. K.

|

tom nr 2

140--155

EN

Maritime transport forms the backbone of international logistics, as it allows for the transfer of bulk and long-haul products. The sophisticated planning required for this form of transportation frequently involves challenges such as unpredictable weather, diverse types of cargo kinds, and changes in port conditions, all of which can raise operational expenses. As a result, the accurate projection of a ship’s total time spent in port, and the anticipation of potential delays, have become critical for effective port activity planning and management. In this work, we aim to develop a port management system based on enhanced prediction and classification algorithms that are capable of precisely forecasting the lengths of ship stays and delays. On both the training and testing datasets, the XGBoost model was found to consistently outperform the alternative approaches in terms of RMSE, MAE, and R2 values for both the turnaround time and waiting period models. When used in the turnaround time model, the XGBoost model had the lowest RMSE of 1.29 during training and 0.5019 during testing, and also achieved the lowest MAE of 0.802 for training and 0.391 for testing. It also had the highest R2 values of 0.9788 during training and 0.9933 during testing. Similarly, in the waiting period model, the XGBoost model outperformed the random forest and decision tree models, with the lowest RMSE, MAE, and greatest R2 values in both the training and testing phases.

2

Strategies for developing logistics centres: technological trends and policy implications

100%

Nguyen M. D. , Ko T. Y. , Rudzki K. , Nguyen H. P. , Pham N. D. K.

|

2023

|

tom nr 4

129--147

EN

Logistics centres are currently performing a key function in the development of countries through their ability to regulate goods, markets, and transport. This is shown by the infrastructure, cost, goods flow, and quality of logistical services provided by these centres. Nevertheless, in developing nations or regions with antiquated logistics infrastructure, conventional logistics centres seem to struggle to manage the volume of commodities passing through them, resulting in persistent congestion and an unsteady flow of goods inside these facilities. This issue poses a challenge to the progress of any nation. The emergence of new technology offers a potential avenue to solve the problems inherent in traditional logistics centres. Most prominently, four technologies (the Internet of Things (IoT), Blockchain, Big Data and Cloud computing) are widely applied in traditional logistics centres. This work has conducted a thorough analysis and evaluation of these new technologies in relation to their respective functions and roles inside a logistics centre. Furthermore, this work proposes difficulties in applying new technologies to logistics centres related to issues such as science, energy, cost, or staff qualifications. Finally, future development directions, related to expanding policies in technological applications, or combining each country’s policies for the logistics industry, are carefully discussed.

3

Role of green logistics in the construction of sustainable supply chains

100%

Pham N. D. K. , Dinh G. H. , Pham H. T. , Kozak J. , Nguyen H. P.

|

2023

|

tom nr 3

191--211

EN

The global supply chain has been growing strongly in recent years. This development brings many benefits to the economy, society, and human resources in each country but also causes a large number of concerns related to the environment since traditional logistics activities in the supply chain have been releasing a significant amount of emissions. For that reason, many solutions have been proposed to deal with these environmental pollution problems. Among these, three promising solutions are expected to completely solve environmental problems in every supply chain: (I) Application of blockchain in the supply chain, (II) Use of renewable energy and alternative fuels, and (III) Design of a closed supply chain. However, it seems to lack a comprehensive study of these solutions aiming to overcome the drawbacks of traditional logistics. Indeed, this work focuses on analyzing and evaluating the three above-mentioned solutions and the impacts of each solution on solving problems related to traditional logistics. More importantly, this work also identifies critical factors and challenges such as policies, laws, awareness, and risks that are found to be remarkable difficulties in the shifting progress of traditional logistics to green logistics. Finally, directions for developing and deploying green solutions to the logistics, supply chain, and shipping sectors toward decarbonization strategies and net-zero goals are discussed in detail.

4

Using Artificial Neural Networks for predicting ship fuel consumption

72%

Nguyen V. G. , Sakthivel R. , Rudzik K. , Kozak J. , Sharma P. , Pham N. D. K. , Nguyen P. Q. P. , Nguyen X. P.

|

tom nr 2

39--60

EN

In marine vessel operations, fuel costs are major operating costs which affect the overall profitability of the maritime transport industry. The effective enhancement of using ship fuel will increase ship operation efficiency. Since ship fuel consumption depends on different factors, such as weather, cruising condition, cargo load, and engine condition, it is difficult to assess the fuel consumption pattern for various types of ships. Most traditional statistical methods do not consider these factors when predicting marine vessel fuel consumption. With technological development, different statistical models have been developed for estimating fuel consumption patterns based on ship data. Artificial Neural Networks (ANN) are some of the most effective artificial methods for modelling and validating marine vessel fuel consumption. The application of ANN in maritime transport improves the accuracy of the regression models developed for analysing interactive relationships between various factors. The present review sheds light on consolidating the works carried out in predicting ship fuel consumption using ANN, with an emphasis on topics such as ANN structure, application and prediction algorithms. Future research directions are also proposed and the present review can be a benchmark for mathematical modelling of ship fuel consumption using ANN.

5

Management strategy for seaports aspiring to green logistical goals of IMO: technology and policy solutions

72%

Le T. T. , Nguyen H. P. , Rudzki K. , Rowiński L. , Bui V. D. , Truong T. H. , Le H. C. , Pham N. D. K.

|

tom nr 2

165--187

EN

Recently, because of serious global challenges including the consumption of energy and climate change, there has been an increase in interest in the environmental effect of port operations and expansion. More interestingly, a strategic tendency in seaport advancement has been to manage the seaport system using a model which balances environmental volatility and economic development demands. An energy efficient management system is regarded as being vital for meeting the strict rules aimed at reducing the environmental pollution caused by port facility activities. Moreover, the enhanced supervision of port system operating methods and technical resolutions for energy utilisation also raise significant issues. In addition, low-carbon ports, as well as green port models, are becoming increasingly popular in seafaring nations. This study comprises a comprehensive assessment of operational methods, cutting-edge technologies for sustainable generation, storage, and transformation of energy, as well as systems of smart grid management, to develop a green seaport system, obtaining optimum operational efficiency and environmental protection. It is thought that using a holistic method and adaptive management, based on a framework of sustainable and green energy, could stimulate creative thinking, consensus building, and cooperation, as well as streamline the regulatory demands associated with port energy management. Although several aspects of sustainability and green energy could increase initial expenditure, they might result in significant life cycle savings due to decreased consumption of energy and output of emissions, as well as reduced operational and maintenance expenses.