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Study On Berth And Anchorage Resource Allocation Based On Ship Arrival Volume

Posted on:2024-08-31Degree:MasterType:Thesis
Country:ChinaCandidate:N PanFull Text:PDF
GTID:2542306929480804Subject:Transportation
Abstract/Summary:PDF Full Text Request
With the increase of port throughput and the development of larger ships,the loading and unloading capacity and service level of ports are also increasing,yet berths and anchorages,as the core facilities affecting the development of port areas,are facing the problems of insufficient resources and uneven distribution.Excessive increase in the construction of berths and anchorages will lead to a large amount of wasted costs and resources,but insufficient construction will increase the dwell time of ships causing congestion in the port area,so a reasonable allocation and utilization of port area resources is crucial.The thesis firstly predicts the ship arrivals and proposes to improve the prediction model by optimizing the whitening coefficients with particle swarm for the shortcomings of gray Markov model in prediction accuracy.Then,the ship arrivals are input into the queuing theory to establish the queuing service model of berths and anchorages in the port area and get the relevant parameters such as the ship’s detention time and queuing length in the port.Finally,the multi-objective resource allocation model with the total cost of the port area and the vessel stay time as the objective function and the shoreline resources and channel passage safety as the constraints is established by combining the relevant costs and parameters of the port area to realize the resource allocation study of the berths and anchorages in the port area,and the following conclusions are obtained:(1)The results show that the prediction accuracy of the grey Markov model based on the particle swarm improvement is optimal,and its average percentage error value is 1.64%,and the average error mean value is reduced by 32%,which confirms the effectiveness of the particle swarm algorithm to improve the grey Markov model,and improves the prediction accuracy to a certain extent,and provides data support for the subsequent resource allocation.(2)Combined with the status quo of the port area and the arrival situation of ships,the multi-objective resource allocation of berths and anchorages in 2021 and 2026 is carried out respectively.The allocation results show that the demand of berths in 2021 is exactly satisfied,but the number of anchorages is short of two,which can be solved through the allocation of anchorages in the comprehensive port area.The berth and anchorage in 2026 cannot meet the demand of ships arriving at the port,so some expansion is needed to meet the balance of supply and demand of port resources and ships arriving at the port.(3)Parametric sensitivity analysis of the configuration results in 2026 reveals that the cost of the port area increases with the increase of ship arrivals,and the ship waiting time fluctuates with the arriving ships;the ship waiting time and the cost of the port area decrease with the increase of loading and unloading efficiency,but the cost will eventually reach stability without further change.Therefore,in order to make the cost as low as possible,the loading and unloading efficiency of berths should be improved,and at the same time,certain anchorages should be equipped,so as to reduce the detention time of ships in port and the possibility of channel congestion,ensure the effective use of port resources,and provide managers with a better basis for decision making.
Keywords/Search Tags:Berths, anchorages, predictive models, queuing theory, Multi-objective optimization
PDF Full Text Request
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