Geodesic
Application of self-gonfiguring genetic algorithm for human resource management
Žurnal Sibirskogo federalʹnogo universiteta. Matematika i fizika, Tome 8 (2015) no. 1, pp. 94-103

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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, genetic algorithm, constrained optimization, self-configuration.
Mots-clés : simulation 
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     title = {Application of self-gonfiguring genetic algorithm for human resource management},
     journal = {\v{Z}urnal Sibirskogo federalʹnogo universiteta. Matematika i fizika},
     pages = {94--103},
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     url = {http://geodesic.mathdoc.fr/item/JSFU_2015_8_1_a11/}
}
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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. Žurnal Sibirskogo federalʹnogo universiteta. Matematika i fizika, Tome 8 (2015) no. 1, pp. 94-103. http://geodesic.mathdoc.fr/item/JSFU_2015_8_1_a11/