Latest revision as of 20:35, 22 March 2021

Abstract

    <jats:p> Determination of efficiency and optimization harbour tug fleet is based on simulation of fleet work and usage for this the methods of ship dynamics and probability theory. Visiting the port transport vessels of possible types is considered as random stream of given intensity. This stream is distributed over the berths. Productivities of berths are given random variables. Random variables are also characteristics of weather conditions in the harbour basin. Tug fleet is represented by the collection of existing port tugs of different types. Work of tugs is determined by operations of approaching to ships, escorting theirs in the near-port waters, posting on the approach channels, transportation within the port waters, berthing, unberthing and going out the ship from the port with the repetition of functioning operations in reverse order. Selection of tugs to service the next arriving or departing ship is dependent from the intensity of the current weather conditions in the port and busyness of tugs in operations with other ships. Work fleet is considered on the conditional time interval of one year. In this time the efficiency of the tug fleet is defined by economic indexes of fulfilment of all towing operations and operations on maintenance tugs. Optimization of the fleet composition is carried out according to the criteria required minimum total bollard pull, low cost and high profit. Based on performed research a program for calculating the efficiency and optimization of the port towing fleet is composed. The program can be adapted to any port with whatever types of tugs.

Document type: Article

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• https://content.sciendo.com/downloadpdf/journals/ttj/19/2/article-p140.pdf under the license https://creativecommons.org/licenses/by-nc-nd

• http://www.degruyter.com/view/j/ttj.2018.19.issue-2/ttj-2018-0012/ttj-2018-0012.xml?format=INT,

https://doaj.org/toc/1407-6179 under the license cc-by-nc-nd

• https://content.sciendo.com/view/journals/ttj/19/2/article-p140.xml,

http://www.degruyter.com/view/j/ttj.2018.19.issue-2/ttj-2018-0012/ttj-2018-0012.pdf,

http://dx.doi.org/10.2478/ttj-2018-0012

• https://content.sciendo.com/view/journals/ttj/19/2/article-p140.xml,

https://academic.microsoft.com/#/detail/2801057500 under the license http://creativecommons.org/licenses/by-nc-nd/4.0