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 existin...

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Main Authors: Harnpornchai, N., Chakpitak, N., Chandarasupsang, T., Tuang-Ath Chaikijkosi, T., Dahal, Keshav P.
Language:en
Published: 2009
Subjects:
Online Access:http://hdl.handle.net/10454/2472
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spelling ndltd-BRADFORD-oai-bradscholars.brad.ac.uk-10454-24722019-08-31T03:02:27Z 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. Human Resource Management (HRM) Human Resource (HR) planning Genetic Algorithms (GA) Multiple constraints Dynamic systems Age distribution 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. 2009-03-12T15:26:04Z 2009-03-12T15:26:04Z 2007 Conference paper published version paper Harnpornchai, N.; Chakpitak, N.; Chandarasupsang, T.; Tuang-Ath Chaikijkosi; Dahal, K. (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, pp.1234 - 1239. http://hdl.handle.net/10454/2472 en http://ieeexplore.ieee.org/search/wrapper.jsp?arnumber=4424611 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.
collection NDLTD
language en
sources NDLTD
topic Human Resource Management (HRM)
Human Resource (HR) planning
Genetic Algorithms (GA)
Multiple constraints
Dynamic systems
Age distribution
spellingShingle Human Resource Management (HRM)
Human Resource (HR) planning
Genetic Algorithms (GA)
Multiple constraints
Dynamic systems
Age distribution
Harnpornchai, N.
Chakpitak, N.
Chandarasupsang, T.
Tuang-Ath Chaikijkosi, T.
Dahal, Keshav P.
Dynamic adjustment of age distribution in Human Resource Management by genetic algorithms.
description 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.
author Harnpornchai, N.
Chakpitak, N.
Chandarasupsang, T.
Tuang-Ath Chaikijkosi, T.
Dahal, Keshav P.
author_facet Harnpornchai, N.
Chakpitak, N.
Chandarasupsang, T.
Tuang-Ath Chaikijkosi, T.
Dahal, Keshav P.
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 2009
url http://hdl.handle.net/10454/2472
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AT tuangathchaikijkosit dynamicadjustmentofagedistributioninhumanresourcemanagementbygeneticalgorithms
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