Building and Using an Ontology of Preference-Based Multiobjective Evolutionary Algorithms
Li L, Yevseyeva I, Basto-Fernandes V, Trautmann H, Jing N, Emmerich M
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.
Keywords
Preference; Evolutionary Multiobjective Optimization; Multicriteria decision making; OWL ontology; Protégé
Cite as
Li, L., Yevseyeva, I., Basto-Fernandes, V., Trautmann, H., Jing, N., & Emmerich, M. (2017). Building and Using an Ontology of Preference-Based Multiobjective Evolutionary Algorithms. In Trautmann, H., Rudolph, G., Klamroth, K., Schütze, O., Wiecek, M., Jin, Y., & Grimme, C. (Eds.),
Evolutionary Multi-Criterion Optimization: 9th International Conference, EMO 2017, Münster, Germany, March 19-22, 2017, Proceedings (pp. 406–421). Cham: Springer International Publishing.
Details
Publication type
Research article (book contribution)
Peer reviewed
Yes
Publication status
Published
Year
2017
Book title
Evolutionary Multi-Criterion Optimization: 9th International Conference, EMO 2017, Münster, Germany, March 19-22, 2017, Proceedings
Editor
Trautmann H, Rudolph G, Klamroth K, Schütze O, Wiecek M, Jin Y, Grimme C
Start page
406
End page
421
Publisher
Springer International Publishing
Place
Cham
Language
English
ISBN
978-3-319-54157-0
DOI
Full text
