Optimizing UAV Trajectories via a Simplified Close Enough TSP Approach
This work addresses trajectory optimization for UAVs, offering incremental improvements in computational efficiency for domain-specific applications.
The paper tackled the Close Enough Traveling Salesman Problem by introducing simplified mathematical formulations and convex constraints to reduce computational complexity, achieving effective resource management without compromising solution quality in real-world instances.
This article explores an approach to addressing the Close Enough Traveling Salesman Problem (CETSP). The objective is to streamline the mathematical formulation by introducing reformulations that approximate the Euclidean distances and simplify the objective function. Additionally, the use of convex sets in the constraint design offers computational benefits. The proposed methodology is empirically validated on real-world CETSP instances, with the aid of computational strategies such as a fragmented CPLEX-based approach. Results demonstrate its effectiveness in managing computational resources without compromising solution quality. Furthermore, the article analyzes the behavior of the proposed mathematical formulations, providing comprehensive insights into their performance.