---
res:
  bibo_abstract:
  - In multi-objective optimization, set-based performance indicators have become
    the state of the art for assessing the quality of Pareto front approximations.
    As a consequence, they are also more and more used within the design of multi-objective
    optimization algorithms. The R2 and the Hypervolume (HV) indicator represent two
    popular examples. In order to understand the behavior and the approximations preferred
    by these indicators and algorithms, a comprehensive knowledge of the indicator’s
    properties is required. Whereas this knowledge is available for the HV, we presented
    a first approach in this direction for the R2 indicator just recently. In this
    paper, we build upon this knowledge and enhance the considerations with respect
    to the integration of preferences into the R2 indicator. More specifically, we
    analyze the effect of the reference point, the domain of the weights, and the
    distribution of weight vectors on the optimization of $\mu$ solutions with respect
    to the R2 indicator. By means of theoretical findings and empirical evidence,
    we show the potentials of these three possibilities using the optimal distribution
    of $\mu$ solutions for exemplary setups.@eng
  bibo_authorlist:
  - foaf_Person:
      foaf_givenName: Tobias
      foaf_name: Wagner, Tobias
      foaf_surname: Wagner
  - 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
  - foaf_Person:
      foaf_givenName: Dimo
      foaf_name: Brockhoff, Dimo
      foaf_surname: Brockhoff
  dct_date: 2013^xs_gYear
  dct_isPartOf:
  - http://id.crossref.org/issn/978-3-642-37140-0
  dct_language: eng
  dct_publisher: Springer Berlin Heidelberg@
  dct_title: Preference Articulation by Means of the R2 Indicator@
...