A Note on the Largest Insertion Algorithm for the Traveling Salesman Problem

ABSTRACT Nearest, Farthest, and Cheapest Insertion are three well‐known polynomial‐time approximation algorithms for the Traveling Salesman Problem (TSP). This paper aims to report on a fourth insertion algorithm, called Largest Insertion, from both a theoretical and an experimental viewpoint. On the theoretical side, the worst‐case performance of the algorithm is studied: In particular, it is shown that there exist instances for which the value of the solution computed by Largest Insertion approaches three times the optimum in the Euclidean plane. On the experimental side, the outcome of computational tests is reported: When compared with the other three insertion algorithms, Largest Insertion scores second on random Euclidean instances and first on large random graphical instances.

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Publication Details

Journal
Networks
Published
2025-09-22
DOI
https://doi.org/10.1002/net.70012
Primary Topic
Optimization and Search Problems
Type
article
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article

A Note on the Largest Insertion Algorithm for the Traveling Salesman Problem

Giovanni Righini, Dario Ostuni
Networks
Optimization and Search Problems
article

A Note on the Largest Insertion Algorithm for the Traveling Salesman Problem

Giovanni Righini, Dario Ostuni
article en

Abstract

ABSTRACT Nearest, Farthest, and Cheapest Insertion are three well‐known polynomial‐time approximation algorithms for the Traveling Salesman Problem (TSP). This paper aims to report on a fourth insertion algorithm, called Largest Insertion, from both a theoretical and an experimental viewpoint. On the theoretical side, the worst‐case performance of the algorithm is studied: In particular, it is shown that there exist instances for which the value of the solution computed by Largest Insertion approaches three times the optimum in the Euclidean plane. On the experimental side, the outcome of computational tests is reported: When compared with the other three insertion algorithms, Largest Insertion scores second on random Euclidean instances and first on large random graphical instances.

NetworksVol. 87(1)
University of Milan (IT)
Openalex Percentile: Top 70%
Optimization and Search Problems
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