The software developed within the scope of this project aims to make the logistics processes of businesses "environmentally friendly and cost-effective." The goals set to achieve this aim are as follows:

• Cost reduction in shipping processes: Developing and expanding optimization algorithms to increase the efficiency of logistics processes.

• Tracking and reducing carbon emissions: Contributing to the reduction of carbon emissions by adding algorithms capable of calculating carbon emissions, accelerating monitoring, raising awareness, and supporting decision-making processes.

• Sustainable and digital logistics management: Ensuring that logistics activities can be easily monitored in a sustainable and digital manner.

 

Strategies for sustainable and smart cities are increasingly being adopted on both national and international levels, making big data algorithm-based technologies essential for their implementation. Financial challenges, such as rising fuel prices, are also driving the growing need to develop solutions that improve logistics efficiency.

The solution developed within the scope of this project uses data such as inventory, road network information (including restrictions), fleet information, vehicle characteristics, and the number of drivers as inputs for the optimization algorithm. Additionally, in terms of big data usage, FCD and GPS data were utilized to calculate travel times, conduct traffic analyses, and measure carbon emissions.

 

The project outcome offers optimization for route, vehicle, and driver assignments by analyzing these inputs and innovative algorithms. Furthermore, it assists companies in taking environmentally friendly steps by reporting the carbon emissions generated during shipments. As a result, an optimization and carbon emission calculation software has been developed to provide an eco-friendly and cost-effective solution for the logistics processes of manufacturing businesses.