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This article is cited in 2 scientific papers (total in 2 papers)
Application of self-gonfiguring genetic algorithm for human resource management
Andrej Škrabaa, Davorin Kofjača, Anja Žnidaršiča, Matjaž Maletiča, Črtomir Rozmanb, Eugene S. Semenkinc, Maria E. Semenkinac, Vladimir V. Stanovovc a Faculty of Organizational Sciences, University of Maribor,
Kidričeva cesta, 55a, SI-4000 Kranj, Slovenia
b Faculty of Agriculture and Life Sciences, University of Maribor,
Pivola, 10, SI-2311 Hoče, Slovenia
c Siberian State Aerospace University, Krasnoyarsky rabochy, 31, Krasnoyarsk, 660014, Russia
Abstract:
This paper describes the problem of human resource management which can appear in many organizations during restructuration periods. The problem is simulated by a dynamic model, similar to a supply chain model with several ranks. The problem of finding the optimal combination of transition coefficients, including the fluctuation coefficients, is transformed into an optimization problem. To solve this problem, a self-configuring genetic algorithm is applied with several constraint handling methods. Additional constraints are defined in order to avoid undesirable oscillations in the system. The results show that this problem can be efficiently solved by the presented methods.
Keywords:
human resources management, simulation, genetic algorithm, constrained optimization, self-configuration.
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UDC:
519.78 Received: 10.11.2014 Received in revised form: 02.12.2014 Accepted: 15.12.2014
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Citation:
Andrej Škraba, Davorin Kofjač, Anja Žnidaršič, Matjaž Maletič, Črtomir Rozman, Eugene S. Semenkin, Maria E. Semenkina, Vladimir V. Stanovov, “Application of self-gonfiguring genetic algorithm for human resource management”, J. Sib. Fed. Univ. Math. Phys., 8:1 (2015), 94–103
Citation in format AMSBIB
\Bibitem{SkrKofZni15}
\by Andrej~{\v S}kraba, Davorin~Kofja{\v{c}}, Anja~{\v Z}nidar{\v s}i{\v{c}}, Matja{\v z}~Maleti{\v{c}}, {\v C}rtomir~Rozman, Eugene~S.~Semenkin, Maria~E.~Semenkina, Vladimir~V.~Stanovov
\paper Application of self-gonfiguring genetic algorithm for human resource management
\jour J. Sib. Fed. Univ. Math. Phys.
\yr 2015
\vol 8
\issue 1
\pages 94--103
\mathnet{http://mi.mathnet.ru/jsfu410}
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http://mi.mathnet.ru/eng/jsfu410 http://mi.mathnet.ru/eng/jsfu/v8/i1/p94
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This publication is cited in the following articles:
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Skraba A., Semenkin E., Kofjac D., Semenkina M., Znidarsic A., Maletic M., Akhmedova Sh., Rozman C., Stanovov V., “Modelling and Optimization of Strictly Hierarchical Manpower System”, Icimco 2015 Proceedings of the 12Th International Conference on Informatics in Control, Automation and Robotics, Vol. 1, eds. Filipe J., Madani K., Gusikhin O., Sasiadek J., IEEE, 2015, 215–222
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D. Zhao, J. Li, Yu. Tan, K. Yang, B. Ge, Ya. Dou, “Optimization adjustment of human resources based on dynamic heterogeneous network”, Physica A, 503 (2018), 45–57
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