This article is cited in 2 papers

Application of self-gonfiguring genetic algorithm for human resource management

Andrej Škraba^a, Davorin Kofjač^a, Anja Žnidaršič^a, Matjaž Maletič^a, Črtomir Rozman^b, Eugene S. Semenkin^c, Maria E. Semenkina^c, Vladimir V. Stanovov<sup>c

a</sup> 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.

UDC: 519.78

Received: 10.11.2014
Received in revised form: 02.12.2014
Accepted: 15.12.2014

Language: English