---
res:
  bibo_abstract:
  - 'Evolutionary algorithms have successfully been applied to evolve problem instances
    that exhibit a significant difference in performance for a given algorithm or
    a pair of algorithms inter alia for the Traveling Salesperson Problem (TSP). Creating
    a large variety of instances is crucial for successful applications in the blooming
    field of algorithm selection. In this paper, we introduce new and creative mutation
    operators for evolving instances of the TSP. We show that adopting those operators
    in an evolutionary algorithm allows for the generation of benchmark sets with
    highly desirable properties: (1) novelty by clear visual distinction to established
    benchmark sets in the field, (2) visual and quantitative diversity in the space
    of TSP problem characteristics, and (3) significant performance differences with
    respect to the restart versions of heuristic state-of-the-art TSP solvers EAX
    and LKH. The important aspect of diversity is addressed and achieved solely by
    the proposed mutation operators and not enforced by explicit diversity preservation.@eng'
  bibo_authorlist:
  - foaf_Person:
      foaf_givenName: Jakob
      foaf_name: Bossek, Jakob
      foaf_surname: Bossek
      foaf_workInfoHomepage: http://www.librecat.org/personId=102979
    orcid: 0000-0002-4121-4668
  - foaf_Person:
      foaf_givenName: Pascal
      foaf_name: Kerschke, Pascal
      foaf_surname: Kerschke
  - foaf_Person:
      foaf_givenName: Aneta
      foaf_name: Neumann, Aneta
      foaf_surname: Neumann
  - foaf_Person:
      foaf_givenName: Markus
      foaf_name: Wagner, Markus
      foaf_surname: Wagner
  - foaf_Person:
      foaf_givenName: Frank
      foaf_name: Neumann, Frank
      foaf_surname: Neumann
  - foaf_Person:
      foaf_givenName: Heike
      foaf_name: Trautmann, Heike
      foaf_surname: Trautmann
      foaf_workInfoHomepage: http://www.librecat.org/personId=100740
    orcid: 0000-0002-9788-8282
  bibo_doi: 10.1145/3299904.3340307
  dct_date: 2019^xs_gYear
  dct_language: eng
  dct_title: Evolving Diverse TSP Instances by Means of Novel and Creative Mutation
    Operators@
...