التفاصيل البيبلوغرافية
| العنوان: |
Seaport throughput forecasting and post COVID-19 recovery policy by using effective decision‐making strategy: A case study of Vietnam ports. |
| المؤلفون: |
Cuong, Truong Ngoc1 (AUTHOR), Kim, Hwan-Seong1 (AUTHOR), You, Sam-Sang1,2 (AUTHOR) ssyou@kmou.ac.kr, Nguyen, Duy Anh3,4 (AUTHOR) |
| المصدر: |
Computers & Industrial Engineering. Jun2022, Vol. 168, pN.PAG-N.PAG. 1p. |
| مصطلحات موضوعية: |
*DECISION making, *SYSTEMS theory, *FORECASTING, *COVID-19, LOTKA-Volterra equations, SLIDING mode control, TIME delay systems, HARBORS |
| مصطلحات جغرافية: |
VIETNAM |
| مستخلص: |
• Lotka-Volterra equations describe dynamics of cooperation and competition. • Seaport throughput forecasting is demonstrated by neural network algorithm. • Control synthesis deals with container throughput dynamics against disruptions. • Novel control approach is validated through case study of Vietnam ports. • Port authorities cope with volatility to improve port performance and reliability. This study deals with the dynamic interactions between seaports and decision-making strategy for seaport operations by utilizing four-dimensional fractional Lotka-Volterra competition model under frequently disrupted by time-delay factor. Nonlinear analysis methods, including equilibrium analysis, stability evaluation, and time series investigation, are intensely explored to describe the cooperation and competition dynamics in maritime logistics. The dynamical analysis indicates that the port competition system shows a complex and highly nonlinear behaviour, notably illustrating unstable equilibria and even chaotic phenomena. Besides, nonlinear dynamical interactions in seaport management have been analysed by exploiting fractional calculus (FC) and system dynamics theory. Novel multi-criteria decision-making strategies realized by the neural network prediction controller (NNC) and adaptive fractional-order super-twisting sliding mode control (AFOSTSM) have been presented for dealing with throughput dynamics under parametric perturbations and external disturbances. Particularly, the active control algorithms are implemented to ensure the recovery strategy for throughput growth of Vietnam ports in the post-coronavirus (COVID-19) pandemic era. The case study has confirmed the efficacy of the proposed strategy by using system dynamics and control theory. The simulation results show that the average growth rates of container throughput can be ensured up to 7.46% by exploiting resilience management scheme. The presented method can be also utilized for providing managerial insights and solutions on efficient port operations. In addition, the control strategies with neural network forecasting can help managers obtain timely and cost-effective decision-making policy for port sustainability against unprecedented impacts on global supply chains related to COVID-19 pandemic. [ABSTRACT FROM AUTHOR] |
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| قاعدة البيانات: |
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