Dynamic adjustment of age distribution in human resource management by genetic algorithms
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 num...
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2014
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th-cmuir.6653943832-9482014-08-29T09:09:58Z Dynamic adjustment of age distribution in human resource management by genetic algorithms Harnpornchai N. Chakpitak N. Chandarasupsang T. Chaikijkosi T.-A. Dahal K. 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. © 2007 IEEE. 2014-08-29T09:09:58Z 2014-08-29T09:09:58Z 2007 Conference Paper 1424413400; 9781424413409 10.1109/CEC.2007.4424611 71533 http://www.scopus.com/inward/record.url?eid=2-s2.0-79955301302&partnerID=40&md5=fecb43af99109aaaab375e94c77ce3e3 http://cmuir.cmu.ac.th/handle/6653943832/948 English |
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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. © 2007 IEEE. |
format |
Conference or Workshop Item |
author |
Harnpornchai N. Chakpitak N. Chandarasupsang T. Chaikijkosi T.-A. Dahal K. |
spellingShingle |
Harnpornchai N. Chakpitak N. Chandarasupsang T. Chaikijkosi T.-A. Dahal K. Dynamic adjustment of age distribution in human resource management by genetic algorithms |
author_facet |
Harnpornchai N. Chakpitak N. Chandarasupsang T. Chaikijkosi T.-A. Dahal K. |
author_sort |
Harnpornchai N. |
title |
Dynamic adjustment of age distribution in human resource management by genetic algorithms |
title_short |
Dynamic adjustment of age distribution in human resource management by genetic algorithms |
title_full |
Dynamic adjustment of age distribution in human resource management by genetic algorithms |
title_fullStr |
Dynamic adjustment of age distribution in human resource management by genetic algorithms |
title_full_unstemmed |
Dynamic adjustment of age distribution in human resource management by genetic algorithms |
title_sort |
dynamic adjustment of age distribution in human resource management by genetic algorithms |
publishDate |
2014 |
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http://www.scopus.com/inward/record.url?eid=2-s2.0-79955301302&partnerID=40&md5=fecb43af99109aaaab375e94c77ce3e3 http://cmuir.cmu.ac.th/handle/6653943832/948 |
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