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Development of Decision Support Tool for Transport Forwarding Company Operating within Netherlands and Italy

This paper investigates the development of a decision support tool for a Latvian transportation company operating in the Dutch and Italian markets. Models and algorithms for optimizing freight routes using Excel and Python are included. Digitalization of logistics processes is recognized as a key to improve efficiency and reduce costs. Two methods for solving the traveling salesman problem were examined and compared: Excel with Solver and Python with the NetworkX library.The methodology involved collecting data from Google My Maps, creating Excel spreadsheets, and developing Python software to automate route optimization. The results showed that both methods improved route planning, reducing time and cost, as well as reducing carbon footprint.The study emphasizes the importance of integrating technologies such as machine learning and big data into logistics to increase flexibility and adaptability. Recommendations were offered to further improve and implement these technologies for sustainable business development and increased competitiveness in international markets.

Author: Anastasija Škaduna

Supervisor: Berdymyrat Ovezmyradov

Degree: Professional Bachelor

Year: 2024

Work Language: English


Development of Trucking Services In Nigeria: Problems and Perspectives

This study delves into the current state of the Nigerian trucking services, aiming to improve efficiency and identify potential areas for growth. We employ a multi-pronged research approach utilizing both quantitative and qualitative data. First, a comprehensive literature review gathers existing knowledge. Second, secondary data analysis examines the current trucking landscape, including its connections with other transportation modes. Third, stakeholder interviews capture diverse perspectives from truck owners, drivers, manufacturers, and policymakers. Fourth, a public survey gauges public opinion and industry potential. Fifth, in-depth case studies compare and analyze three distinct trucking companies with unique business models with a SWOT analysis to evaluate each company considering their economic value contribution. Finally, the research utilizes a network model to optimize logistics and efficiency. Results are presented visually and discussed in detail. Recommendations for improvement are formulated based on the findings. The study concludes by acknowledging its strengths and limitations.

Author: Olusola Adepoju Ademola

Supervisor: Berdymyrat Ovezmyradov

Degree: Master

Year: 2024

Work Language: English


Improvement of Logistics Sector in Uzbekistan Through Integration of Smart Technologies

The primary aim of this research paper is to comprehensively evaluate the integration of smart technologies in Uzbekistan's logistics sector. For achieving the research aim the author used a mixed method combining both qualitative and quantitative. As for the primary data, the author of the research used a survey among professionals in logistics and potential users to understand their awareness, perceived benefits, and concerns regarding smart technology integration in Uzbekistan. At the end of the research based on the results the author provides conclusions and recommendations on the integration of smart technologies in Uzbekistan's logistics sector

Author: Otabek Usmanov

Supervisor: Berdymyrat Ovezmyradov

Degree: Master

Year: 2024

Work Language: English

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