Salvato in:
Dettagli Bibliografici
Autori principali: Lee, Jae Hyeok, Hwang, Taekang, Kwon, Changhyun
Natura: Preprint
Pubblicazione: 2026
Soggetti:
Accesso online:https://arxiv.org/abs/2603.00328
Tags: Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
_version_ 1866917300551024640
author Lee, Jae Hyeok
Hwang, Taekang
Kwon, Changhyun
author_facet Lee, Jae Hyeok
Hwang, Taekang
Kwon, Changhyun
contents The asymptotic behavior of the optimal TSP tour length is well known from the classical Beardwood--Halton--Hammersley theorem. We extend this result to the Traveling Salesman Problem with Drone (TSPD), a cooperative routing problem in which a truck and a drone jointly serve customers. Using a subadditive Euclidean functional framework, we establish the existence of an almost sure limit for the optimal TSPD makespan scaled by the square root of the problem size. We derive explicit upper and lower bounds for the speed-scaled Euclidean TSPD model: upper bounds are obtained via structured ring-based tour constructions and Monte Carlo evaluation, while lower bounds are derived from a parametric approach and known bounds on the Euclidean TSP constant. Computational results illustrate how tight the bounds are. We also derive and discuss lower bounds for the Rectilinear--Euclidean mixed TSPD model, in which truck travel is measured by the rectilinear distance and drone travel by the Euclidean distance.
format Preprint
id arxiv_https___arxiv_org_abs_2603_00328
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Asymptotic Bounds for the Traveling Salesman Problem with Drone
Lee, Jae Hyeok
Hwang, Taekang
Kwon, Changhyun
Optimization and Control
Discrete Mathematics
The asymptotic behavior of the optimal TSP tour length is well known from the classical Beardwood--Halton--Hammersley theorem. We extend this result to the Traveling Salesman Problem with Drone (TSPD), a cooperative routing problem in which a truck and a drone jointly serve customers. Using a subadditive Euclidean functional framework, we establish the existence of an almost sure limit for the optimal TSPD makespan scaled by the square root of the problem size. We derive explicit upper and lower bounds for the speed-scaled Euclidean TSPD model: upper bounds are obtained via structured ring-based tour constructions and Monte Carlo evaluation, while lower bounds are derived from a parametric approach and known bounds on the Euclidean TSP constant. Computational results illustrate how tight the bounds are. We also derive and discuss lower bounds for the Rectilinear--Euclidean mixed TSPD model, in which truck travel is measured by the rectilinear distance and drone travel by the Euclidean distance.
title Asymptotic Bounds for the Traveling Salesman Problem with Drone
topic Optimization and Control
Discrete Mathematics
url https://arxiv.org/abs/2603.00328