A manpower planning model based on length of service under varying class sizes

Gupta, Arindam; Ghosal, Anindita

doi:10.1007/s12597-013-0162-1

Cited by 1 publication

(1 citation statement)

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“…Unsurprisingly, the human resource planning requires advanced quantitative methods to provide proper results. Gupta and Ghosal (2014) applied stochastic modelling for determination of the appropriate time of promotion considering the survival rates in different classes. They have considered varying size classes and indicated, that the main goal of an employee in an organization is to get a promotion to the next grade.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2016

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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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Section: Introductionmentioning

confidence: 99%