Application of Hybrid Swarming Algorithm on a UAV Regional Logistics Distribution

Area of Science:

• Optimization Algorithms
• Computational Intelligence
• Logistics and Transportation

Background:

• The Traveling Salesman Problem (TSP) is a critical challenge in logistics and operations research.
• Existing algorithms often face limitations in speed and solution accuracy for complex routing scenarios.
• Efficient pathfinding is essential for timely delivery services, especially during public health crises.

Purpose of the Study:

• To develop a hybrid optimization algorithm integrating Ant Colony System (ACS) and Physarum Polycephalum (PP) for improved Traveling Salesman Problem (TSP) solutions.
• To introduce genetic algorithm (GA) operations and Van der Waals forces into the pathfinding and pheromone updating mechanisms.
• To validate the algorithm's efficacy and practical applicability through simulations and a real-world contactless delivery scheme.

Main Methods:

• Hybridization of Ant Colony System (ACS) and Physarum Polycephalum (PP) algorithms.
• Integration of crossover and mutation operations from Genetic Algorithms (GA) into path search.
• Application of Van der Waals force principles for pheromone updating.
• Comparative simulation analysis against other mainstream routing algorithms.

Main Results:

• The proposed hybrid algorithm significantly outperforms existing methods in both solution quality and computational speed.
• Demonstrated superior performance in finding globally optimal paths for the Traveling Salesman Problem.
• Achieved faster and more accurate route planning compared to conventional algorithms.

Conclusions:

• The hybrid ACS-PP-GA algorithm offers a robust and efficient solution for the Traveling Salesman Problem.
• The algorithm's practical application in a contactless Unmanned Aerial Vehicle (UAV) delivery scheme during the COVID-19 pandemic highlights its real-world viability.
• This research provides a foundation for advanced, fast, and accurate routing solutions in logistics and delivery services.