---
_id: '48893'
abstract:
- lang: eng
  text: Computing diverse sets of high-quality solutions has gained increasing attention
    among the evolutionary computation community in recent years. It allows practitioners
    to choose from a set of high-quality alternatives. In this paper, we employ a
    population diversity measure, called the high-order entropy measure, in an evolutionary
    algorithm to compute a diverse set of high-quality solutions for the Traveling
    Salesperson Problem. In contrast to previous studies, our approach allows diversifying
    segments of tours containing several edges based on the entropy measure. We examine
    the resulting evolutionary diversity optimisation approach precisely in terms
    of the final set of solutions and theoretical properties. Experimental results
    show significant improvements compared to a recently proposed edge-based diversity
    optimisation approach when working with a large population of solutions or long
    segments.
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. Entropy-Based Evolutionary Diversity
    Optimisation for the Traveling Salesperson Problem. In: <i>Proceedings of the
    Genetic and Evolutionary Computation Conference</i>. GECCO’21. Association for
    Computing Machinery; 2021:600–608. doi:<a href="https://doi.org/10.1145/3449639.3459384">10.1145/3449639.3459384</a>'
  apa: Nikfarjam, A., Bossek, J., Neumann, A., &#38; Neumann, F. (2021). Entropy-Based
    Evolutionary Diversity Optimisation for the Traveling Salesperson Problem. <i>Proceedings
    of the Genetic and Evolutionary Computation Conference</i>, 600–608. <a href="https://doi.org/10.1145/3449639.3459384">https://doi.org/10.1145/3449639.3459384</a>
  bibtex: '@inproceedings{Nikfarjam_Bossek_Neumann_Neumann_2021, place={New York,
    NY, USA}, series={GECCO’21}, title={Entropy-Based Evolutionary Diversity Optimisation
    for the Traveling Salesperson Problem}, DOI={<a href="https://doi.org/10.1145/3449639.3459384">10.1145/3449639.3459384</a>},
    booktitle={Proceedings of the Genetic and Evolutionary Computation Conference},
    publisher={Association for Computing Machinery}, author={Nikfarjam, Adel and Bossek,
    Jakob and Neumann, Aneta and Neumann, Frank}, year={2021}, pages={600–608}, collection={GECCO’21}
    }'
  chicago: 'Nikfarjam, Adel, Jakob Bossek, Aneta Neumann, and Frank Neumann. “Entropy-Based
    Evolutionary Diversity Optimisation for the Traveling Salesperson Problem.” In
    <i>Proceedings of the Genetic and Evolutionary Computation Conference</i>, 600–608.
    GECCO’21. New York, NY, USA: Association for Computing Machinery, 2021. <a href="https://doi.org/10.1145/3449639.3459384">https://doi.org/10.1145/3449639.3459384</a>.'
  ieee: 'A. Nikfarjam, J. Bossek, A. Neumann, and F. Neumann, “Entropy-Based Evolutionary
    Diversity Optimisation for the Traveling Salesperson Problem,” in <i>Proceedings
    of the Genetic and Evolutionary Computation Conference</i>, 2021, pp. 600–608,
    doi: <a href="https://doi.org/10.1145/3449639.3459384">10.1145/3449639.3459384</a>.'
  mla: Nikfarjam, Adel, et al. “Entropy-Based Evolutionary Diversity Optimisation
    for the Traveling Salesperson Problem.” <i>Proceedings of the Genetic and Evolutionary
    Computation Conference</i>, Association for Computing Machinery, 2021, pp. 600–608,
    doi:<a href="https://doi.org/10.1145/3449639.3459384">10.1145/3449639.3459384</a>.
  short: 'A. Nikfarjam, J. Bossek, A. Neumann, F. Neumann, in: Proceedings of the
    Genetic and Evolutionary Computation Conference, Association for Computing Machinery,
    New York, NY, USA, 2021, pp. 600–608.'
date_created: 2023-11-14T15:59:00Z
date_updated: 2023-12-13T10:50:06Z
department:
- _id: '819'
doi: 10.1145/3449639.3459384
extern: '1'
keyword:
- evolutionary algorithms
- evolutionary diversity optimisation
- high-order entropy
- traveling salesperson problem
language:
- iso: eng
page: 600–608
place: New York, NY, USA
publication: Proceedings of the Genetic and Evolutionary Computation Conference
publication_identifier:
  isbn:
  - 978-1-4503-8350-9
publisher: Association for Computing Machinery
series_title: GECCO’21
status: public
title: Entropy-Based Evolutionary Diversity Optimisation for the Traveling Salesperson
  Problem
type: conference
user_id: '102979'
year: '2021'
...