Last mile delivery problem
Work description
The work plan for the AI-Driven Optimization for Sustainable Last Mile Delivery (AIO-TacitR) project is structured around advancing solutions to the Vehicle Routing Problem (VRP) by leveraging Artificial Intelligence, Machine Learning, and Generative AI to improve sustainability and real-time adaptability in urban logistics. The project begins with foundational activities such as literature review, data collection, and preprocessing to build a robust knowledge base. It then advances to developing and refining AI models that integrate zone characteristics, traffic conditions, weather, and driver feedback. These models aim not only to reduce delivery times and operational costs but also to minimize environmental impacts, aligning with sustainability goals. The plan emphasizes iterative development, incorporating feedback loops from testing and environmental analysis to continuously improve performance. Over the timeline, the project follows a phased approach: Year 1 focuses on groundwork—research, data preparation, and initial AI model prototypes. Year 2 emphasizes refinement, prototype testing, and detailed environmental impact assessments, while Year 3 prioritizes integration of AI systems into partner logistics operations, user experience design, validation, and large-scale dissemination of results. Cross-cutting activities like project management, stakeholder engagement, and sustainability reporting ensure the alignment of research outputs with industry needs and societal goals. The structured plan ultimately seeks to bridge the gap between theoretical optimization models and real-world delivery challenges, setting a foundation for greener, more efficient, and socially responsible logistics solutions.
Academic Qualifications
Education in Industrial Engineering, Informatics Engineering, Mechanical Engineering, Computer Science, Civil Engineering or related area.
Minimum profile required
Experience in the following skill(s):- Programming in Python- Ability to work in group, high autonomy, and organization-Experience in working with datasets- Basic knowledge of ETL processFluent in Portuguese and English.
Preference factors
- Knowledge of data science and engineering - Experience in developing machine learning models and data analysis - Experience in working with big data
Application Period
Since 16 Oct 2025 to 29 Oct 2025
Centre
Industrial Engineering and Management