Loading...
Dynamic adjustment of age distribution in Human Resource Management by genetic algorithms
Harnpornchai, N. Chakpitak, N. Chandarasupsang, T. Tuang-Ath Chaikijkosi, T. Dahal, Keshav P.
Harnpornchai, N.
Chakpitak, N.
Chandarasupsang, T.
Tuang-Ath Chaikijkosi, T.
Dahal, Keshav P.
Publication Date
2007
End of Embargo
Supervisor
Rights
Copyright © [2007] IEEE. Reprinted from IEEE Congress on
Evolutionary Computation, 2007 (CEC 2007).
This material is posted here with permission of the IEEE. Such permission of the
IEEE does not in any way imply IEEE endorsement of any of the University of
Bradford's products or services. Internal or personal use of this material is
permitted. However, permission to reprint/republish this material for advertising
or promotional purposes or for creating new collective works for resale or
redistribution must be obtained from the IEEE by writing to pubspermissions@
ieee.org.
By choosing to view this document, you agree to all provisions of the copyright
laws protecting it.
Peer-Reviewed
Yes
Open Access status
Accepted for publication
Institution
Department
Awarded
Embargo end date
Additional title
Abstract
Adjustment of a given age distribution to a desired
age distribution within a required time frame is dynamically
performed for the purpose of Human Resource (HR) planning
in Human Resource Management (HRM). The adjustment
process is carried out by adding the adjustment magnitudes to
the existing number of employees at the selected age groups on
the yearly basis. A model of a discrete dynamical system is
employed to emulate the evolution of the age distribution used
under the adjustment process. Genetic Algorithms (GA) is
applied for determining the adjustment magnitudes that
influence the dynamics of the system. An interesting aspect
of the problem lies in the high number of constraints;
though the constraints are fundamental, they are
considerably higher in number than in many other
optimization problems. An adaptive penalty scheme is
proposed for handling the constraints. Numerical
examples show that GA with the utilized adaptive penalty
scheme provides potential means for HR planning in HRM.
Version
Published version
Citation
Harnpornchai N, Chakpitak N, Chandarasupsang T et al (2007) Dynamic adjustment of age distribution in Human
Resource Management by genetic algorithms. In: IEEE Congress on Evolutionary
Computation (CEC 2007), 25-28 Sept. 2007, Singapore: 1234 - 1239.
Link to publisher’s version
Link to published version
Link to Version of Record
Type
Conference paper