---
_id: '48892'
abstract:
- lang: eng
  text: Evolutionary algorithms based on edge assembly crossover (EAX) constitute
    some of the best performing incomplete solvers for the well-known traveling salesperson
    problem (TSP). Often, it is desirable to compute not just a single solution for
    a given problem, but a diverse set of high quality solutions from which a decision
    maker can choose one for implementation. Currently, there are only a few approaches
    for computing a diverse solution set for the TSP. Furthermore, almost all of them
    assume that the optimal solution is known. In this paper, we introduce evolutionary
    diversity optimisation (EDO) approaches for the TSP that find a diverse set of
    tours when the optimal tour is known or unknown. We show how to adopt EAX to not
    only find a high-quality solution but also to maximise the diversity of the population.
    The resulting EAX-based EDO approach, termed EAX-EDO is capable of obtaining diverse
    high-quality tours when the optimal solution for the TSP is known or unknown.
    A comparison to existing approaches shows that they are clearly outperformed by
    EAX-EDO.
author:
- first_name: Adel
  full_name: Nikfarjam, Adel
  last_name: Nikfarjam
- first_name: Jakob
  full_name: Bossek, Jakob
  id: '102979'
  last_name: Bossek
  orcid: 0000-0002-4121-4668
- first_name: Aneta
  full_name: Neumann, Aneta
  last_name: Neumann
- first_name: Frank
  full_name: Neumann, Frank
  last_name: Neumann
citation:
  ama: 'Nikfarjam A, Bossek J, Neumann A, Neumann F. Computing Diverse Sets of High
    Quality TSP Tours by EAX-based Evolutionary Diversity Optimisation. In: <i>Proceedings
    of the 16th ACM}/SIGEVO Conference on Foundations of Genetic Algorithms</i>. Association
    for Computing Machinery; 2021:1–11.'
  apa: Nikfarjam, A., Bossek, J., Neumann, A., &#38; Neumann, F. (2021). Computing
    Diverse Sets of High Quality TSP Tours by EAX-based Evolutionary Diversity Optimisation.
    In <i>Proceedings of the 16th ACM}/SIGEVO Conference on Foundations of Genetic
    Algorithms</i> (pp. 1–11). Association for Computing Machinery.
  bibtex: '@inbook{Nikfarjam_Bossek_Neumann_Neumann_2021, place={New York, NY, USA},
    title={Computing Diverse Sets of High Quality TSP Tours by EAX-based Evolutionary
    Diversity Optimisation}, booktitle={Proceedings of the 16th ACM}/SIGEVO Conference
    on Foundations of Genetic Algorithms}, publisher={Association for Computing Machinery},
    author={Nikfarjam, Adel and Bossek, Jakob and Neumann, Aneta and Neumann, Frank},
    year={2021}, pages={1–11} }'
  chicago: 'Nikfarjam, Adel, Jakob Bossek, Aneta Neumann, and Frank Neumann. “Computing
    Diverse Sets of High Quality TSP Tours by EAX-Based Evolutionary Diversity Optimisation.”
    In <i>Proceedings of the 16th ACM}/SIGEVO Conference on Foundations of Genetic
    Algorithms</i>, 1–11. New York, NY, USA: Association for Computing Machinery,
    2021.'
  ieee: 'A. Nikfarjam, J. Bossek, A. Neumann, and F. Neumann, “Computing Diverse Sets
    of High Quality TSP Tours by EAX-based Evolutionary Diversity Optimisation,” in
    <i>Proceedings of the 16th ACM}/SIGEVO Conference on Foundations of Genetic Algorithms</i>,
    New York, NY, USA: Association for Computing Machinery, 2021, pp. 1–11.'
  mla: Nikfarjam, Adel, et al. “Computing Diverse Sets of High Quality TSP Tours by
    EAX-Based Evolutionary Diversity Optimisation.” <i>Proceedings of the 16th ACM}/SIGEVO
    Conference on Foundations of Genetic Algorithms</i>, Association for Computing
    Machinery, 2021, pp. 1–11.
  short: 'A. Nikfarjam, J. Bossek, A. Neumann, F. Neumann, in: Proceedings of the
    16th ACM}/SIGEVO Conference on Foundations of Genetic Algorithms, Association
    for Computing Machinery, New York, NY, USA, 2021, pp. 1–11.'
date_created: 2023-11-14T15:59:00Z
date_updated: 2023-12-13T10:49:59Z
department:
- _id: '819'
extern: '1'
keyword:
- edge assembly crossover (EAX)
- evolutionary algorithms
- evolutionary diversity optimisation (EDO)
- traveling salesperson problem (TSP)
language:
- iso: eng
page: 1–11
place: New York, NY, USA
publication: Proceedings of the 16th ACM}/SIGEVO Conference on Foundations of Genetic
  Algorithms
publication_identifier:
  isbn:
  - 978-1-4503-8352-3
publisher: Association for Computing Machinery
status: public
title: Computing Diverse Sets of High Quality TSP Tours by EAX-based Evolutionary
  Diversity Optimisation
type: book_chapter
user_id: '102979'
year: '2021'
...