Abstract
This paper shows how state space models for human resource planning may be extended from linear and goal-programming formulations to cover the case where manpower demands and available resources for future periods are not known with certainty. Under reasonable assumptions, the problem can be treated as a multi-period stochastic program with simple recourse. Normal and Beta probability distributions are fitted to the right hand sides, and the equivalent determinstic programme solved using convex separable programming. An application of this methodology to a military human resource planning problem is described. Solution times for the stochastic model compare favourably with those for a goal-programming model of the same human resource system.
Similar content being viewed by others
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
Martel, A., Price, W. Stochastic Programming Applied to Human Resource Planning. J Oper Res Soc 32, 187–196 (1981). https://doi.org/10.1057/jors.1981.41
Published:
Issue Date:
DOI: https://doi.org/10.1057/jors.1981.41