---
_id: '46365'
abstract:
- lang: eng
  text: Despite the intrinsic hardness of the Traveling Salesperson Problem (TSP)
    heuristic solvers, e.g., LKH+restart and EAX+restart, are remarkably successful
    in generating satisfactory or even optimal solutions. However, the reasons for
    their success are not yet fully understood. Recent approaches take an analytical
    viewpoint and try to identify instance features, which make an instance hard or
    easy to solve. We contribute to this area by generating instance sets for couples
    of TSP algorithms A and B by maximizing/minimizing their performance difference
    in order to generate instances which are easier to solve for one solver and much
    harder to solve for the other. This instance set offers the potential to identify
    key features which allow to distinguish between the problem hardness classes of
    both algorithms.
author:
- first_name: Jakob
  full_name: Bossek, Jakob
  id: '102979'
  last_name: Bossek
  orcid: 0000-0002-4121-4668
- first_name: Heike
  full_name: Trautmann, Heike
  id: '100740'
  last_name: Trautmann
  orcid: 0000-0002-9788-8282
citation:
  ama: 'Bossek J, Trautmann H. Evolving Instances for Maximizing Performance Differences
    of State-of-The-Art Inexact TSP Solvers. In: Festa P, Sellmann M, Vanschoren J,
    eds. <i>Learning and Intelligent Optimization</i>. Vol 10079. Lecture Notes in
    Computer Science. Springer International Publishing; 2016:48–59. doi:<a href="https://doi.org/10.1007/978-3-319-50349-3_4">10.1007/978-3-319-50349-3_4</a>'
  apa: Bossek, J., &#38; Trautmann, H. (2016). Evolving Instances for Maximizing Performance
    Differences of State-of-The-Art Inexact TSP Solvers. In P. Festa, M. Sellmann,
    &#38; J. Vanschoren (Eds.), <i>Learning and Intelligent Optimization</i> (Vol.
    10079, pp. 48–59). Springer International Publishing. <a href="https://doi.org/10.1007/978-3-319-50349-3_4">https://doi.org/10.1007/978-3-319-50349-3_4</a>
  bibtex: '@inproceedings{Bossek_Trautmann_2016, place={Ischia, Italy}, series={Lecture
    Notes in Computer Science}, title={Evolving Instances for Maximizing Performance
    Differences of State-of-The-Art Inexact TSP Solvers}, volume={10079}, DOI={<a
    href="https://doi.org/10.1007/978-3-319-50349-3_4">10.1007/978-3-319-50349-3_4</a>},
    booktitle={Learning and Intelligent Optimization}, publisher={Springer International
    Publishing}, author={Bossek, Jakob and Trautmann, Heike}, editor={Festa, P and
    Sellmann, M and Vanschoren, J}, year={2016}, pages={48–59}, collection={Lecture
    Notes in Computer Science} }'
  chicago: 'Bossek, Jakob, and Heike Trautmann. “Evolving Instances for Maximizing
    Performance Differences of State-of-The-Art Inexact TSP Solvers.” In <i>Learning
    and Intelligent Optimization</i>, edited by P Festa, M Sellmann, and J Vanschoren,
    10079:48–59. Lecture Notes in Computer Science. Ischia, Italy: Springer International
    Publishing, 2016. <a href="https://doi.org/10.1007/978-3-319-50349-3_4">https://doi.org/10.1007/978-3-319-50349-3_4</a>.'
  ieee: 'J. Bossek and H. Trautmann, “Evolving Instances for Maximizing Performance
    Differences of State-of-The-Art Inexact TSP Solvers,” in <i>Learning and Intelligent
    Optimization</i>, 2016, vol. 10079, pp. 48–59, doi: <a href="https://doi.org/10.1007/978-3-319-50349-3_4">10.1007/978-3-319-50349-3_4</a>.'
  mla: Bossek, Jakob, and Heike Trautmann. “Evolving Instances for Maximizing Performance
    Differences of State-of-The-Art Inexact TSP Solvers.” <i>Learning and Intelligent
    Optimization</i>, edited by P Festa et al., vol. 10079, Springer International
    Publishing, 2016, pp. 48–59, doi:<a href="https://doi.org/10.1007/978-3-319-50349-3_4">10.1007/978-3-319-50349-3_4</a>.
  short: 'J. Bossek, H. Trautmann, in: P. Festa, M. Sellmann, J. Vanschoren (Eds.),
    Learning and Intelligent Optimization, Springer International Publishing, Ischia,
    Italy, 2016, pp. 48–59.'
date_created: 2023-08-04T15:10:58Z
date_updated: 2024-06-10T11:58:25Z
department:
- _id: '34'
- _id: '819'
doi: 10.1007/978-3-319-50349-3_4
editor:
- first_name: P
  full_name: Festa, P
  last_name: Festa
- first_name: M
  full_name: Sellmann, M
  last_name: Sellmann
- first_name: J
  full_name: Vanschoren, J
  last_name: Vanschoren
intvolume: '     10079'
language:
- iso: eng
page: 48–59
place: Ischia, Italy
publication: Learning and Intelligent Optimization
publication_identifier:
  isbn:
  - 978-3-319-50348-6
publisher: Springer International Publishing
series_title: Lecture Notes in Computer Science
status: public
title: Evolving Instances for Maximizing Performance Differences of State-of-The-Art
  Inexact TSP Solvers
type: conference
user_id: '15504'
volume: 10079
year: '2016'
...