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



Publication type
Chapter in Book

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

Pages range
406-421

Publisher
Springer International Publishing

Place
Cham

ISBN
978-3-319-54157-0

DOI

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