Optimizing cost-effectiveness in a stochastic Markov manpower planning system under control by recruitment

Tim De Feyter (), Marie-Anne Guerry () and Komarudin ()
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Tim De Feyter: KU Leuven
Marie-Anne Guerry: Vrije Universiteit Brussel
Komarudin: Universitas Indonesia

Annals of Operations Research, 2017, vol. 253, issue 1, No 7, 117-131

Abstract: Abstract The present paper proposes a mathematical model and algorithm for optimizing cost-effectiveness in a stochastic manpower planning system under control by recruitment. More specifically, we suggest a multi-objective model that simultaneously addresses two objectives, namely minimizing the cost and maximizing the desirability degree of the attained personnel structure. In a stochastic environment, the uncontrollable parameters of the manpower model (i.e. internal transitions and wastage) are random variables. We suggest a scenario approach in order to cope with this uncertainty. The optimization problem under study is formulated as a mixed integer program. Further, in order to decrease the computing time in solving the optimization problem, we show that the optimal recruitment strategy has some properties that enable narrowing the solution space.

Keywords: Manpower planning; Markov models; Fuzzy sets; Stochastic models (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s10479-016-2311-4

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