Building and Using an Ontology of Preference-Based Multiobjective Evolutionary Algorithms

Li L, Yevseyeva I, Basto-Fernandes V, Trautmann H, Jing N, Emmerich M


Zusammenfassung
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.

Schlüsselwörter
Preference; Evolutionary Multiobjective Optimization; Multicriteria decision making; OWL ontology; Protégé



Publikationstyp
Buchbeitrag (Sammel-, Herausgeberband)

Begutachtet
Ja

Publikationsstatus
Veröffentlicht

Jahr
2017

Buchtitel
Evolutionary Multi-Criterion Optimization: 9th International Conference, EMO 2017, Münster, Germany, March 19-22, 2017, Proceedings

Herausgeber
Trautmann H, Rudolph G, Klamroth K, Schütze O, Wiecek M, Jin Y, Grimme C

Seiten
406-421

Verlag
Springer International Publishing

Ort
Cham

ISBN
978-3-319-54157-0

DOI

Gesamter Text