• DocumentCode
    2752388
  • Title

    An ontological multi-criteria optimization system for Workforce Management

  • Author

    Cimitile, Marta ; Gaeta, Matteo ; Loia, Vincenzo

  • Author_Institution
    Unitelma Sapienza Univ., Rome, Italy
  • fYear
    2012
  • fDate
    10-15 June 2012
  • Firstpage
    1
  • Lastpage
    7
  • Abstract
    Workforce Management (WFM) is becoming a core decisional approach for optimizing different enterprise processes such as operational activities needed to maintain a high production rate. However, in order to solve complex optimization problems it is necessary to analyze and deal with a plethora of distributed and semantically different information defining the collection of criteria from which enterprise activities depend. For this reason, this paper introduces a novel WFM system that, by using an ontological representation of knowledge related to the different aspects of an enterprise activity, exploits a multi-criteria decision making approach for selecting the most suitable strategies to face WFM issues.
  • Keywords
    decision making; ontologies (artificial intelligence); optimisation; WFM; enterprise activity; enterprise process; knowledge representation; multicriteria decision making approach; ontological multicriteria optimization system; plethora; workforce management; Companies; Data acquisition; Ontologies; Optimization; Semantics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems (FUZZ-IEEE), 2012 IEEE International Conference on
  • Conference_Location
    Brisbane, QLD
  • ISSN
    1098-7584
  • Print_ISBN
    978-1-4673-1507-4
  • Electronic_ISBN
    1098-7584
  • Type

    conf

  • DOI
    10.1109/FUZZ-IEEE.2012.6251158
  • Filename
    6251158