---
res:
  bibo_abstract:
  - State of the Art inexact solvers of the NP-hard Traveling Salesperson Problem
    (TSP) are known to mostly yield high-quality solutions in reasonable computation
    times. With the purpose of understanding different levels of instance difficulties,
    instances for the current State of the Art heuristic TSP solvers LKH+restart and
    EAX+restart are presented which are evolved using a sophisticated evolutionary
    algorithm. More specifically, the performance differences of the respective solvers
    are maximized resulting in instances which are easier to solve for one solver
    and much more difficult for the other. Focusing on both optimization directions,
    instance features are identified which characterize both types of instances and
    increase the understanding of solver performance differences.@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: Heike
      foaf_name: Trautmann, Heike
      foaf_surname: Trautmann
      foaf_workInfoHomepage: http://www.librecat.org/personId=100740
    orcid: 0000-0002-9788-8282
  bibo_doi: 10.1007/978-3-319-49130-1_1
  bibo_volume: 10037
  dct_date: 2016^xs_gYear
  dct_isPartOf:
  - http://id.crossref.org/issn/978-3-319-49129-5
  dct_language: eng
  dct_publisher: Springer@
  dct_title: Understanding Characteristics of Evolved Instances for State-of-the-Art
    Inexact TSP Solvers with Maximum Performance Difference@
...