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Hybridization of Stochastic Local Search and Genetic Algorithm for Human Resource Planning Management

Author

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  • Škraba Andrej
  • Kofjač Davorin

    (University of Maribor, Faculty of Organizational Sciences, Kidričeva cesta 55a, SI-4000 Kranj, Slovenia)

  • Stanovov Vladimir
  • Semenkin Eugene

    (Reshetnev Siberian State Aerospace University, Institute of Computer Science and Telecommunications, 31 »Krasnoyarskiy Rabochiy« ave., Krasnoyarsk, 660037, Russian Federation)

Abstract

Background and Purpose: The restructuring of human resources in an organization is addressed in this paper, because human resource planning is a crucial process in every organization. Here, a strict hierarchical structure of the organization is of concern here, for which a change in a particular class of the structure influences classes that follow it. Furthermore, a quick adaptation of the structure to the desired state is required, where oscillations in transitions between classes are not desired, because they slow down the process of adaptation. Therefore, optimization of such a structure is highly complex, and heuristic methods are needed to approach such problems to address them properly.

Suggested Citation

  • Škraba Andrej & Kofjač Davorin & Stanovov Vladimir & Semenkin Eugene, 2016. "Hybridization of Stochastic Local Search and Genetic Algorithm for Human Resource Planning Management," Organizacija, Sciendo, vol. 49(1), pages 42-54, February.
    • Handle: RePEc:vrs:organi:v:49:y:2016:i:1:p:42-54:n:5
    DOI: 10.1515/orga-2016-0005
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