DocumentCode :
2779430
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 :
business data processing; decision making; human resource management; ontologies (artificial intelligence); optimisation; WFM system; complex optimization problem; enterprise activity; enterprise process; multicriteria decision making approach; ontological knowledge representation; ontological multicriteria optimization system; operational activity; production rate; workforce management; Companies; Data acquisition; Ontologies; Optimization; Semantics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation (CEC), 2012 IEEE Congress on
Conference_Location :
Brisbane, QLD
Print_ISBN :
978-1-4673-1510-4
Electronic_ISBN :
978-1-4673-1508-1
Type :
conf
DOI :
10.1109/CEC.2012.6252901
Filename :
6252901
Link To Document :
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