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  • Information Support for Planning the Transportation of Oversized cargo Using Machine Learning (on the Example of JSC “NIPIGAZ”)

Information Support for Planning the Transportation of Oversized cargo Using Machine Learning (on the Example of JSC “NIPIGAZ”)

Student: Meschiryakova Nataliya

Supervisor: Gleb Zakhodiakin

Faculty: Graduate School of Business

Educational Programme: Digital Logistics and Supply Chain Management (Master)

Year of Graduation: 2021

The purpose of this work is to create a solution to optimize the planning process for ground transportation of oversized cargo, in particular, the selection of the type of vehicle. The main tasks were the analysis of the company's position in the market, the analysis of the logistics system and business processes for planning the ground transportation of OS/HL, the analysis of world practices in the application of machine learning in the field of transport logistics, the development of a software solution in Python using machine learning algorithms, analysis the effectiveness of the implementation of this software solution in the company's business processes. As a result, a software solution was developed that allows to reduce the time and financial costs during the initial planning of the transportation of OS/HL in the implementation of industrial construction projects in the oil and gas industry.

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