Using the AIS Data to enhance smart port congestion optimizing model Subtitle as needed (paper subtitle)

Nowadays, ports are in need to maximize their incomes, and this based on the fierce competition. For this reason, all ports stakeholders should be involved to contribute in the design and the development of a policy of scheduling and priority.This project owned by the Vessel Call Service Planning Service in the port of Tanger Med as the "Tanger Med Port Authority", and it output was to report the summarized the work done and the methods behind it.The main goal is to develop a simulator model that includes all kind of operations and the operational process by choosing the appropriate KPIs that are fully reflecting the congestion transferred by port vesselsFirst, it aims to define the operating assumptions and the fundamental concepts on which our simulation model will be based and to present the data that were used for the implementation of the simulation as well as the origin of these data.Secondly, it aims to validate and calibrate the model by presenting some improvements that could be made to the simulator in order to make it more precise and more representative and to ensure automation of the processing of inputs and outputs. While towards the end we conclude with the presentation of congestion situations, the results obtained and their use in decision making.AIS data is another factor has been added to help in getting best results, this helped in vessels planification in/out predictive process while automating the use of our simulator with the AIS Data receipt from SatelliteThis part of project is in to give the smart aspect to our simulator results by using smart technology.

A State-Dependent Approximation Method for Estimating Truck Queue Length at Marine Terminals

As international trade and freight volumes increase, there is a growing port congestion problem, leading to the long truck queues at US marine terminal gates. To address this problem, some countermeasures have been proposed and implemented for reducing truck queue length at marine terminals. To assess the effectiveness of these countermeasures, a method for accurately estimating terminal gate truck queue length is needed. This study developed a new method, named the state-dependent approximation method, for estimating the truck queue length at marine terminals. Based on the simulation of the truck queuing system, it was found that it takes several hours for the truck queue length to reach its steady state, and neglecting the queue formation (queue dispersion) processes will cause overestimation (underestimation) of truck queue length. The developed model can take into account the queue formation and dispersion processes, and it can be used to estimate the truck queue length caused by short-term oversaturation at marine terminals. For model evaluation, a simulation-based case study was conducted to evaluate the prediction accuracy of the developed model by comparing its results with the simulated queue lengths and the results of other four existing methods, including the fluid flow model, the M/M/S queuing model, and a simulation-based regression model developed a previous study. The evaluation results indicate that the developed model outperformed the other four modeling methods for different states of queue formation and dispersion processes. In addition, this new method can accurately estimate the truck queue length caused by the short-term system oversaturation during peak hours. Therefore, it will be useful for assessing the effectiveness of the countermeasures that are targeted at reducing the peak-hour congestion at marine terminals.

Container Slot Allocation for Time-Sensitive Cargo in Maritime Transportation: A One-Phase Model with consideration of Port Congestion

This paper studies a container slot allocation problem with dynamic pricing for time-sensitive cargo considering port congestion. Time-sensitive cargo calls for express delivery as soon as possible, and hence a new pricing pattern is proposed considering port congestion. To solve the slot allocation with dynamic pricing issue, a one-phase allocation model which is from different points of view on slot allocation strategy is proposed to formulate this problem. Finally, numerical examples are carried out to test the applicability of the proposed model and solution algorithm.

Determinant Port-related Factors Affecting the Flow of Shipping Trade and Logistics in Nigerian Seaports

The need to eliminate bottlenecks to port operations in Nigeria was a fundamental goal of the port privatization about 2 decades ago. Current trends in ports management; however, suggest existence of numerous inefficiency challenges reflected in long ship turnaround time, increasing trend of cargo dwell time, high cargo pilferage risk rate, poor condition of port infrastructure and superstructure, multiple charges and government agencies, cumbersome cargo clearance & examination procedures, port congestion related delays particularly in Apapa and Onne ports, etc. The study identifies the decisive port-related factors constraining the flow of shipping trade in Nigerian ports using a survey to obtain data on the influence of the identified factors on the flow of shipping trade in Nigerian ports. The Principal Component Analysis (PCA) was used to analyze the data obtained. The results indicate that high cargo pilferage risk profile, long ship turnaround time and increasing trend of cargo dwell time constitute the significant port-related factors constraining the flow of shipping in Nigerian ports. It can be concluded that terminal operators should prioritize solutions to the problems of high cargo pilferage risk profile, long ship turnaround time and increasing cargo dwell time, which constitute the major constraints to the flow of shipping trade.