---
_id: '48894'
abstract:
- lang: eng
  text: Recently different evolutionary computation approaches have been developed
    that generate sets of high quality diverse solutions for a given optimisation
    problem. Many studies have considered diversity 1) as a mean to explore niches
    in behavioural space (quality diversity) or 2) to increase the structural differences
    of solutions (evolutionary diversity optimisation). In this study, we introduce
    a co-evolutionary algorithm to simultaneously explore the two spaces for the multi-component
    traveling thief problem. The results show the capability of the co-evolutionary
    algorithm to achieve significantly higher diversity compared to the baseline evolutionary
    diversity algorithms from the literature.
author:
- first_name: Adel
  full_name: Nikfarjam, Adel
  last_name: Nikfarjam
- first_name: Aneta
  full_name: Neumann, Aneta
  last_name: Neumann
- first_name: Jakob
  full_name: Bossek, Jakob
  id: '102979'
  last_name: Bossek
  orcid: 0000-0002-4121-4668
- first_name: Frank
  full_name: Neumann, Frank
  last_name: Neumann
citation:
  ama: 'Nikfarjam A, Neumann A, Bossek J, Neumann F. Co-Evolutionary Diversity Optimisation
    for the Traveling Thief Problem. In: Rudolph G, Kononova AV, Aguirre H, Kerschke
    P, Ochoa G, Tu\v sar T, eds. <i>Parallel Problem Solving from Nature (PPSN XVII)</i>.
    Lecture Notes in Computer Science. Springer International Publishing; 2022:237–249.
    doi:<a href="https://doi.org/10.1007/978-3-031-14714-2_17">10.1007/978-3-031-14714-2_17</a>'
  apa: Nikfarjam, A., Neumann, A., Bossek, J., &#38; Neumann, F. (2022). Co-Evolutionary
    Diversity Optimisation for the Traveling Thief Problem. In G. Rudolph, A. V. Kononova,
    H. Aguirre, P. Kerschke, G. Ochoa, &#38; T. Tu\v sar (Eds.), <i>Parallel Problem
    Solving from Nature (PPSN XVII)</i> (pp. 237–249). Springer International Publishing.
    <a href="https://doi.org/10.1007/978-3-031-14714-2_17">https://doi.org/10.1007/978-3-031-14714-2_17</a>
  bibtex: '@inproceedings{Nikfarjam_Neumann_Bossek_Neumann_2022, place={Cham}, series={Lecture
    Notes in Computer Science}, title={Co-Evolutionary Diversity Optimisation for
    the Traveling Thief Problem}, DOI={<a href="https://doi.org/10.1007/978-3-031-14714-2_17">10.1007/978-3-031-14714-2_17</a>},
    booktitle={Parallel Problem Solving from Nature (PPSN XVII)}, publisher={Springer
    International Publishing}, author={Nikfarjam, Adel and Neumann, Aneta and Bossek,
    Jakob and Neumann, Frank}, editor={Rudolph, Günter and Kononova, Anna V. and Aguirre,
    Hernán and Kerschke, Pascal and Ochoa, Gabriela and Tu\v sar, Tea}, year={2022},
    pages={237–249}, collection={Lecture Notes in Computer Science} }'
  chicago: 'Nikfarjam, Adel, Aneta Neumann, Jakob Bossek, and Frank Neumann. “Co-Evolutionary
    Diversity Optimisation for the Traveling Thief Problem.” In <i>Parallel Problem
    Solving from Nature (PPSN XVII)</i>, edited by Günter Rudolph, Anna V. Kononova,
    Hernán Aguirre, Pascal Kerschke, Gabriela Ochoa, and Tea Tu\v sar, 237–249. Lecture
    Notes in Computer Science. Cham: Springer International Publishing, 2022. <a href="https://doi.org/10.1007/978-3-031-14714-2_17">https://doi.org/10.1007/978-3-031-14714-2_17</a>.'
  ieee: 'A. Nikfarjam, A. Neumann, J. Bossek, and F. Neumann, “Co-Evolutionary Diversity
    Optimisation for the Traveling Thief Problem,” in <i>Parallel Problem Solving
    from Nature (PPSN XVII)</i>, 2022, pp. 237–249, doi: <a href="https://doi.org/10.1007/978-3-031-14714-2_17">10.1007/978-3-031-14714-2_17</a>.'
  mla: Nikfarjam, Adel, et al. “Co-Evolutionary Diversity Optimisation for the Traveling
    Thief Problem.” <i>Parallel Problem Solving from Nature (PPSN XVII)</i>, edited
    by Günter Rudolph et al., Springer International Publishing, 2022, pp. 237–249,
    doi:<a href="https://doi.org/10.1007/978-3-031-14714-2_17">10.1007/978-3-031-14714-2_17</a>.
  short: 'A. Nikfarjam, A. Neumann, J. Bossek, F. Neumann, in: G. Rudolph, A.V. Kononova,
    H. Aguirre, P. Kerschke, G. Ochoa, T. Tu\v sar (Eds.), Parallel Problem Solving
    from Nature (PPSN XVII), Springer International Publishing, Cham, 2022, pp. 237–249.'
date_created: 2023-11-14T15:59:00Z
date_updated: 2023-12-13T10:49:51Z
department:
- _id: '819'
doi: 10.1007/978-3-031-14714-2_17
editor:
- first_name: Günter
  full_name: Rudolph, Günter
  last_name: Rudolph
- first_name: Anna V.
  full_name: Kononova, Anna V.
  last_name: Kononova
- first_name: Hernán
  full_name: Aguirre, Hernán
  last_name: Aguirre
- first_name: Pascal
  full_name: Kerschke, Pascal
  last_name: Kerschke
- first_name: Gabriela
  full_name: Ochoa, Gabriela
  last_name: Ochoa
- first_name: Tea
  full_name: Tu\v sar, Tea
  last_name: Tu\v sar
extern: '1'
keyword:
- Co-evolutionary algorithms
- Evolutionary diversity optimisation
- Quality diversity
- Traveling thief problem
language:
- iso: eng
page: 237–249
place: Cham
publication: Parallel Problem Solving from Nature (PPSN XVII)
publication_identifier:
  isbn:
  - 978-3-031-14714-2
publication_status: published
publisher: Springer International Publishing
series_title: Lecture Notes in Computer Science
status: public
title: Co-Evolutionary Diversity Optimisation for the Traveling Thief Problem
type: conference
user_id: '102979'
year: '2022'
...
---
_id: '48876'
abstract:
- lang: eng
  text: In recent years, Evolutionary Algorithms (EAs) have frequently been adopted
    to evolve instances for optimization problems that pose difficulties for one algorithm
    while being rather easy for a competitor and vice versa. Typically, this is achieved
    by either minimizing or maximizing the performance difference or ratio which serves
    as the fitness function. Repeating this process is useful to gain insights into
    strengths/weaknesses of certain algorithms or to build a set of instances with
    strong performance differences as a foundation for automatic per-instance algorithm
    selection or configuration. We contribute to this branch of research by proposing
    fitness-functions to evolve instances that show large performance differences
    for more than just two algorithms simultaneously. As a proof-of-principle, we
    evolve instances of the multi-component Traveling Thief Problem (TTP) for three
    incomplete TTP-solvers. Our results point out that our strategies are promising,
    but unsurprisingly their success strongly relies on the algorithms’ performance
    complementarity.
author:
- first_name: Jakob
  full_name: Bossek, Jakob
  id: '102979'
  last_name: Bossek
  orcid: 0000-0002-4121-4668
- first_name: Markus
  full_name: Wagner, Markus
  last_name: Wagner
citation:
  ama: 'Bossek J, Wagner M. Generating Instances with Performance Differences for
    More than Just Two Algorithms. In: <i>Proceedings of the Genetic and Evolutionary
    Computation Conference Companion</i>. GECCO’21. Association for Computing Machinery;
    2021:1423–1432. doi:<a href="https://doi.org/10.1145/3449726.3463165">10.1145/3449726.3463165</a>'
  apa: Bossek, J., &#38; Wagner, M. (2021). Generating Instances with Performance
    Differences for More than Just Two Algorithms. <i>Proceedings of the Genetic and
    Evolutionary Computation Conference Companion</i>, 1423–1432. <a href="https://doi.org/10.1145/3449726.3463165">https://doi.org/10.1145/3449726.3463165</a>
  bibtex: '@inproceedings{Bossek_Wagner_2021, place={New York, NY, USA}, series={GECCO’21},
    title={Generating Instances with Performance Differences for More than Just Two
    Algorithms}, DOI={<a href="https://doi.org/10.1145/3449726.3463165">10.1145/3449726.3463165</a>},
    booktitle={Proceedings of the Genetic and Evolutionary Computation Conference
    Companion}, publisher={Association for Computing Machinery}, author={Bossek, Jakob
    and Wagner, Markus}, year={2021}, pages={1423–1432}, collection={GECCO’21} }'
  chicago: 'Bossek, Jakob, and Markus Wagner. “Generating Instances with Performance
    Differences for More than Just Two Algorithms.” In <i>Proceedings of the Genetic
    and Evolutionary Computation Conference Companion</i>, 1423–1432. GECCO’21. New
    York, NY, USA: Association for Computing Machinery, 2021. <a href="https://doi.org/10.1145/3449726.3463165">https://doi.org/10.1145/3449726.3463165</a>.'
  ieee: 'J. Bossek and M. Wagner, “Generating Instances with Performance Differences
    for More than Just Two Algorithms,” in <i>Proceedings of the Genetic and Evolutionary
    Computation Conference Companion</i>, 2021, pp. 1423–1432, doi: <a href="https://doi.org/10.1145/3449726.3463165">10.1145/3449726.3463165</a>.'
  mla: Bossek, Jakob, and Markus Wagner. “Generating Instances with Performance Differences
    for More than Just Two Algorithms.” <i>Proceedings of the Genetic and Evolutionary
    Computation Conference Companion</i>, Association for Computing Machinery, 2021,
    pp. 1423–1432, doi:<a href="https://doi.org/10.1145/3449726.3463165">10.1145/3449726.3463165</a>.
  short: 'J. Bossek, M. Wagner, in: Proceedings of the Genetic and Evolutionary Computation
    Conference Companion, Association for Computing Machinery, New York, NY, USA,
    2021, pp. 1423–1432.'
date_created: 2023-11-14T15:58:57Z
date_updated: 2023-12-13T10:47:41Z
department:
- _id: '819'
doi: 10.1145/3449726.3463165
extern: '1'
keyword:
- evolutionary algorithms
- evolving instances
- fitness function
- instance hardness
- traveling thief problem (TTP)
language:
- iso: eng
page: 1423–1432
place: New York, NY, USA
publication: Proceedings of the Genetic and Evolutionary Computation Conference Companion
publication_identifier:
  isbn:
  - 978-1-4503-8351-6
publisher: Association for Computing Machinery
series_title: GECCO’21
status: public
title: Generating Instances with Performance Differences for More than Just Two Algorithms
type: conference
user_id: '102979'
year: '2021'
...
---
_id: '48852'
abstract:
- lang: eng
  text: The Traveling Salesperson Problem (TSP) is one of the best-known combinatorial
    optimisation problems. However, many real-world problems are composed of several
    interacting components. The Traveling Thief Problem (TTP) addresses such interactions
    by combining two combinatorial optimisation problems, namely the TSP and the Knapsack
    Problem (KP). Recently, a new problem called the node weight dependent Traveling
    Salesperson Problem (W-TSP) has been introduced where nodes have weights that
    influence the cost of the tour. In this paper, we compare W-TSP and TTP. We investigate
    the structure of the optimised tours for W-TSP and TTP and the impact of using
    each others fitness function. Our experimental results suggest (1) that the W-TSP
    often can be solved better using the TTP fitness function and (2) final W-TSP
    and TTP solutions show different distributions when compared with optimal TSP
    or weighted greedy solutions.
author:
- 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: 'Bossek J, Neumann A, Neumann F. Optimising Tours for the Weighted Traveling
    Salesperson Problem and the Traveling Thief Problem: A Structural Comparison of
    Solutions. In: <i>Parallel Problem Solving from Nature (PPSN XVI)</i>. Springer-Verlag;
    2020:346–359. doi:<a href="https://doi.org/10.1007/978-3-030-58112-1_24">10.1007/978-3-030-58112-1_24</a>'
  apa: 'Bossek, J., Neumann, A., &#38; Neumann, F. (2020). Optimising Tours for the
    Weighted Traveling Salesperson Problem and the Traveling Thief Problem: A Structural
    Comparison of Solutions. <i>Parallel Problem Solving from Nature (PPSN XVI)</i>,
    346–359. <a href="https://doi.org/10.1007/978-3-030-58112-1_24">https://doi.org/10.1007/978-3-030-58112-1_24</a>'
  bibtex: '@inproceedings{Bossek_Neumann_Neumann_2020, place={Berlin, Heidelberg},
    title={Optimising Tours for the Weighted Traveling Salesperson Problem and the
    Traveling Thief Problem: A Structural Comparison of Solutions}, DOI={<a href="https://doi.org/10.1007/978-3-030-58112-1_24">10.1007/978-3-030-58112-1_24</a>},
    booktitle={Parallel Problem Solving from Nature (PPSN XVI)}, publisher={Springer-Verlag},
    author={Bossek, Jakob and Neumann, Aneta and Neumann, Frank}, year={2020}, pages={346–359}
    }'
  chicago: 'Bossek, Jakob, Aneta Neumann, and Frank Neumann. “Optimising Tours for
    the Weighted Traveling Salesperson Problem and the Traveling Thief Problem: A
    Structural Comparison of Solutions.” In <i>Parallel Problem Solving from Nature
    (PPSN XVI)</i>, 346–359. Berlin, Heidelberg: Springer-Verlag, 2020. <a href="https://doi.org/10.1007/978-3-030-58112-1_24">https://doi.org/10.1007/978-3-030-58112-1_24</a>.'
  ieee: 'J. Bossek, A. Neumann, and F. Neumann, “Optimising Tours for the Weighted
    Traveling Salesperson Problem and the Traveling Thief Problem: A Structural Comparison
    of Solutions,” in <i>Parallel Problem Solving from Nature (PPSN XVI)</i>, 2020,
    pp. 346–359, doi: <a href="https://doi.org/10.1007/978-3-030-58112-1_24">10.1007/978-3-030-58112-1_24</a>.'
  mla: 'Bossek, Jakob, et al. “Optimising Tours for the Weighted Traveling Salesperson
    Problem and the Traveling Thief Problem: A Structural Comparison of Solutions.”
    <i>Parallel Problem Solving from Nature (PPSN XVI)</i>, Springer-Verlag, 2020,
    pp. 346–359, doi:<a href="https://doi.org/10.1007/978-3-030-58112-1_24">10.1007/978-3-030-58112-1_24</a>.'
  short: 'J. Bossek, A. Neumann, F. Neumann, in: Parallel Problem Solving from Nature
    (PPSN XVI), Springer-Verlag, Berlin, Heidelberg, 2020, pp. 346–359.'
date_created: 2023-11-14T15:58:54Z
date_updated: 2023-12-13T10:44:54Z
department:
- _id: '819'
doi: 10.1007/978-3-030-58112-1_24
extern: '1'
keyword:
- Evolutionary algorithms
- Node weight dependent TSP
- Traveling Thief Problem
language:
- iso: eng
page: 346–359
place: Berlin, Heidelberg
publication: Parallel Problem Solving from Nature (PPSN XVI)
publication_identifier:
  isbn:
  - 978-3-030-58111-4
publication_status: published
publisher: Springer-Verlag
status: public
title: 'Optimising Tours for the Weighted Traveling Salesperson Problem and the Traveling
  Thief Problem: A Structural Comparison of Solutions'
type: conference
user_id: '102979'
year: '2020'
...