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Autore principale: Bederina, Hiba
Natura: Preprint
Pubblicazione: 2025
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Accesso online:https://arxiv.org/abs/2507.03775
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author Bederina, Hiba
author_facet Bederina, Hiba
contents 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.
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publishDate 2025
record_format arxiv
spellingShingle Optimizing UAV Trajectories via a Simplified Close Enough TSP Approach
Bederina, Hiba
Artificial Intelligence
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.
title Optimizing UAV Trajectories via a Simplified Close Enough TSP Approach
topic Artificial Intelligence
url https://arxiv.org/abs/2507.03775