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