Building and Using an Ontology of Preference-Based Multiobjective Evolutionary Algorithms Li, L Yevseyeva, I Basto-Fernandes, V Trautmann, Heike Jing, N Emmerich, M Trautmann, H Rudolph, G Klamroth, K Schütze, O Wiecek, M Jin, Y Grimme, C 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. Springer International Publishing 2017 info:eu-repo/semantics/bookPart doc-type:bookPart text http://purl.org/coar/resource_type/c_3248 https://ris.uni-paderborn.de/record/46356 Li L, Yevseyeva I, Basto-Fernandes V, Trautmann H, Jing N, Emmerich M. Building and Using an Ontology of Preference-Based Multiobjective Evolutionary Algorithms. In: Trautmann H, Rudolph G, Klamroth K, et al., eds. <i>Evolutionary Multi-Criterion Optimization: 9$^th$ International Conference, EMO 2017, Münster, Germany, March 19-22, 2017, Proceedings</i>. Springer International Publishing; 2017:406–421. doi:<a href="https://doi.org/10.1007/978-3-319-54157-0_28">10.1007/978-3-319-54157-0_28</a> eng info:eu-repo/semantics/altIdentifier/doi/10.1007/978-3-319-54157-0_28 info:eu-repo/semantics/altIdentifier/isbn/978-3-319-54157-0 info:eu-repo/semantics/closedAccess