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

100%

Škraba A. , Stanovov V. , Semenkin E. , Kofjač D.

nr 1

42-54

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.

Gepsus: simulation-based decision making system for air pollution accidents

63%

Stojanović R. , Škraba A. , Berkowicz S. , Amicis R. D. , Elhanani D. , Conti G. , Kofjač D. , Dragović M. , Lekić N. , Nikolić G.

nr 5

200-210

We describe a GIS-based real-time system for emergency response and management of air pollution accidents in an urban area. The system architecture emphasises the integration of meteorological, chemical and GIS data, dispersion modeling, decision-making and geo-spatial visualization. The threat zones, unsafe areas and safe traffic routes are obtained using an improved Gaussian plume model with a decision-making module and then exported to the Google Earth browser via “kml” file format. Several simulation scenarios were conducted and verified for notable industrial sites in Montenegro using recorded meteorological data. The results demonstrate that emergency response authorities can use the proposed methodology and system as a cost effective and accurate support tool in case of industrial or deliberate air pollution incidents.