Optimizing UAV Trajectories via a Simplified Close Enough TSP Approach

TL;DR

This paper presents a simplified and computationally efficient approach to solving the Close Enough Traveling Salesman Problem (CETSP) by reformulating the problem and leveraging convex sets, validated through real-world instances.

Contribution

Introduces a reformulated CETSP approach using convex sets and approximation techniques, improving computational efficiency while maintaining solution quality.

Findings

Effective management of computational resources

Maintains solution quality with simplified formulations

Provides insights into formulation performance

Abstract

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.