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Modelling recruitment training in mathematical human resource planning
Author(s) -
Georgiou A. C.,
Tsantas N.
Publication year - 2002
Publication title -
applied stochastic models in business and industry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.413
H-Index - 40
eISSN - 1526-4025
pISSN - 1524-1904
DOI - 10.1002/asmb.454
Subject(s) - incentive , order (exchange) , operations research , computer science , workforce , human resources , government (linguistics) , markov chain , class (philosophy) , training (meteorology) , work (physics) , resource allocation , business , operations management , economics , microeconomics , finance , engineering , artificial intelligence , management , economic growth , mechanical engineering , computer network , linguistics , philosophy , physics , machine learning , meteorology
This paper deals with mathematical human resource planning; more specifically, it suggests a new model for a manpower‐planning system. In general, we study a k ‐classed hierarchical system where the workforce demand at each time period is satisfied through internal mobility and recruitment. The motivation for this work is based on various European Union incentives, which promote regional or local government assistance programs that could be exploited by firms not only for hiring and training newcomers, but also to improve the skills and knowledge of their existing personnel. In this respect, in our augmented mobility model we establish a new ‘training/standby’ class, which serves as a manpower inventory position for potential recruits. This class, which may very well be internal or external to the system, is incorporated into the framework of a non‐homogeneous Markov chain model. Furthermore, cost objectives are employed using the goal‐programming approach, under different operating assumptions, in order to minimize the operational cost in the presence of system's constraints and regulations. Copyright © 2002 John Wiley & Sons, Ltd.