AI-Driven Multi-Objective UAV Route Optimization
Unmanned Aerial Vehicles have proven to enhance customer service and increase efficiency in supply chain management. They offer greater flexibility, ease of operation, and bypass traffic congestions by flying directly between nodes. This paper presents an innovative version of the Team Orienteering Problem with Time Windows and Charging Stations. The proposed model integrates various optimization approaches, including heuristics and AI-driven methods. The primary objectives are to maximize service rewards, minimize total travel distance, and mitigate out-of-charge incidents. Experiments are conducted to demonstrate the competency of the applied AI-enabled approach in various scenarios.
Authors
- Ashwin Devanga
- Sahil Belsare
- Mohammad Dehghanimohammadabadai
Institutions
- Northeastern University (US)
Publication Details
- Published
- 2024-12-15
- DOI
- https://doi.org/10.1109/wsc63780.2024.10838909
- Primary Topic
- Robotic Path Planning Algorithms
- Type
- article
- Field-Weighted Citation Impact
- 0.00