
Description
The Tour Data+ project aims to reduce the frictions encountered by postal workers during package delivery by bridging the gap between automatically generated delivery plans and real-world conditions. Current optimization algorithms, while effective, often overlook factors such as weather conditions or roadworks, leading to manual adjustments by employees. The project focuses on the automatic detection and classification of these deviations to enhance systems with the knowledge of field workers.
Experts/Researchers/Institutions:
- Prof. Denis Lalanne (University of Fribourg)
- Dr. Simon Ruffieux (University of Fribourg)
- Dr. Ilyes Kadri (University of Fribourg)
Why it matters:
This project goes beyond classical optimization by integrating workers› feedback into the algorithms. By combining AI with human expertise, it enables more efficient planning and improved human-machine collaboration. Without this augmented approach, real-time adaptation and delivery optimization would not be as accurate or effective.
Funding:
Innosuisse