| Title: | Hybridization of stochastic local search and genetic algorithm for human resource planning management |
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| Authors: | ID Škraba, Andrej (Author)
ID Stanovov, Vladimir (Author)
ID Semenkin, Eugene (Author)
ID Kofjač, Davorin (Author) |
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| Files: |  Organizacija_2016_Skraba_et_al._Hybridization_of_Stochastic_Local_Search_and_Genetic_Algorithm_for_Human_Resource_Planning_Management.pdf (474,90 KB)
MD5: 8B8C6D49512F53A2DD5F06154FC93145
 http://www.degruyter.com/view/j/orga.2016.49.issue-1/orga-2016-0005/orga-2016-0005.xml
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| Language: | English |
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| Work type: | Scientific work |
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| Typology: | 1.01 - Original Scientific Article |
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| Organization: | FOV - Faculty of Organizational Sciences in Kranj
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| 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.
Design/Methodology/Approach: The hierarchical human resources structure is modeled according to the principles of System Dynamics. Optimization of the structure is performed with an algorithm that combines stochastic local search and genetic algorithms.
Results: The developed algorithm was tested on three scenarios; each scenario exhibits a different dynamic in achieving the desired state of the human resource structure. The results show that the developed algorithm has successfully optimized the model parameters to achieve the desired structure of human resources quickly.
Conclusion: We have presented the mathematical model and optimization algorithm to tackle the restructuring of human resources for strict hierarchical organizations. With the developed algorithm, we have successfully achieved the desired organizational structure in all three cases, without the undesired oscillations in the transitions between classes and in the shortest possible time. |
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| Keywords: | stochastic local search, system dynamics, human resources, simulation |
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| Publication status: | Published |
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| Publication version: | Version of Record |
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| Year of publishing: | 2016 |
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| Number of pages: | str. 42-54 |
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| Numbering: | Letn. 49, št. 1 |
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| PID: | 20.500.12556/DKUM-65413  |
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| ISSN: | 1318-5454 |
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| UDC: | 004.94 |
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| ISSN on article: | 1318-5454 |
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| COBISS.SI-ID: | 7526419 |
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| DOI: | 10.1515/orga-2016-005 |
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| NUK URN: | URN:SI:UM:DK:YAKBZNAW |
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| Publication date in DKUM: | 04.04.2017 |
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| Views: | 1300 |
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| Downloads: | 383 |
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| Metadata: |    |
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| Categories: | Misc.
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