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

  • Longmei Li
  • Iryna Yevseyeva
  • Vitor Basto-Fernandes
  • Heike Trautmann
  • Ning Jing
  • Michael Emmerich
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10173)

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 

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Longmei Li
    • 1
    • 2
  • Iryna Yevseyeva
    • 3
  • Vitor Basto-Fernandes
    • 4
    • 5
  • Heike Trautmann
    • 6
  • Ning Jing
    • 1
  • Michael Emmerich
    • 2
  1. 1.School of Electronic Science and EngineeringNational University of Defense TechnologyChangshaChina
  2. 2.Leiden Institute of Advanced Computer ScienceLeiden UniversityLeidenThe Netherlands
  3. 3.Faculty of Technology, School of Computer Science and InformaticsDe Montfort UniversityLeicesterUK
  4. 4.Instituto Universitário de Lisboa (ISCTE-IUL)University Institute of Lisbon, ISTAR-IULLisbonPortugal
  5. 5.School of Technology and Management, Computer Science and Communications Research CentrePolytechnic Institute of LeiriaLeiriaPortugal
  6. 6.Department of Information SystemsUniversity of MünsterMünsterGermany

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