@inbook{46356,
  abstract     = {{Integrating user preferences in Evolutionary Multiobjective Optimization (EMO) is currently a prevalent research topic. There is a large variety of preference handling methods (originated from Multicriteria decision making, MCDM) and EMO methods, which have been combined in various ways. This paper proposes a Web Ontology Language (OWL) ontology to model and systematize the knowledge of preference-based multiobjective evolutionary algorithms (PMOEAs). Detailed procedure is given on how to build and use the ontology with the help of Protégé. Different use-cases, including training new learners, querying and reasoning are exemplified and show remarkable benefit for both EMO and MCDM communities.}},
  author       = {{Li, L and Yevseyeva, I and Basto-Fernandes, V and Trautmann, Heike and Jing, N and Emmerich, M}},
  booktitle    = {{Evolutionary Multi-Criterion Optimization: 9$^th$ International Conference, EMO 2017, Münster, Germany, March 19-22, 2017, Proceedings}},
  editor       = {{Trautmann, H and Rudolph, G and Klamroth, K and Schütze, O and Wiecek, M and Jin, Y and Grimme, C}},
  isbn         = {{978-3-319-54157-0}},
  pages        = {{406–421}},
  publisher    = {{Springer International Publishing}},
  title        = {{{Building and Using an Ontology of Preference-Based Multiobjective Evolutionary Algorithms}}},
  doi          = {{10.1007/978-3-319-54157-0_28}},
  year         = {{2017}},
}