Maintainability of manpower system with restricted recruitment

Ossai, E. O.

doi:10.4314/gjmas.v12i1.11

Cited by 2 publications

(2 citation statements)

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“…However, variations in control methods have been explored in the literature, including the concept of pressure in states introduced by [17] and restricted recruitment as discussed in [18]. Control theory in the context of semi-Markov processes has received limited attention.…”

Section: Introductionmentioning

confidence: 99%

Attainability for Markov and Semi-Markov Chains

Verbeken,

Guerry

2024

Mathematics

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When studying Markov chain models and semi-Markov chain models, it is useful to know which state vectors n, where each component ni represents the number of entities in the state Si, can be maintained or attained. This question leads to the definitions of maintainability and attainability for (time-homogeneous) Markov chain models. Recently, the definition of maintainability was extended to the concept of state reunion maintainability (SR-maintainability) for semi-Markov chains. Within the framework of semi-Markov chains, the states are subdivided further into seniority-based states. State reunion maintainability assesses the maintainability of the distribution across states. Following this idea, we introduce the concept of state reunion attainability, which encompasses the potential of a system to attain a specific distribution across the states after uniting the seniority-based states into the underlying states. In this paper, we start by extending the concept of attainability for constant-sized Markov chain models to systems that are subject to growth or contraction. Afterwards, we introduce the concepts of attainability and state reunion attainability for semi-Markov chain models, using SR-maintainability as a starting point. The attainable region, as well as the state reunion attainable region, are described as the convex hull of their respective vertices, and properties of these regions are investigated.

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Section: Introductionmentioning

confidence: 99%

Attainability for Markov and Semi-Markov Chains

Verbeken,

Guerry

2024

Mathematics

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“…Hence, control through recruitment is often favored because it can be implemented without immediate repercussions for those currently employed Bartholomew [1967]. However, minor adaptations concerning the means of control, such as the use of the concept of pressure in the grades, which was introduced in [Kalamatianou, 1987] or the use of restricted recruitment as in [Ossai, 2013], were considered throughout the literature. Additionally, [Georgiou, 1992] introduced the notion of partial maintainability, which entails the need to retain a portion of the population structure while allowing for flexibility and variability in another portion.…”

Section: Introductionmentioning

confidence: 99%

Discrete Time Hybrid Semi-Markov Models in Manpower Planning

Verbeken

Guerry

2021

Mathematics

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Discrete time Markov models are used in a wide variety of social sciences. However, these models possess the memoryless property, which makes them less suitable for certain applications. Semi-Markov models allow for more flexible sojourn time distributions, which can accommodate for duration of stay effects. An overview of differences and possible obstacles regarding the use of Markov and semi-Markov models in manpower planning was first given by Valliant and Milkovich (1977). We further elaborate on their insights and introduce hybrid semi-Markov models for open systems with transition-dependent sojourn time distributions. Hybrid semi-Markov models aim to reduce model complexity in terms of the number of parameters to be estimated by only taking into account duration of stay effects for those transitions for which it is useful. Prediction equations for the stock vector are derived and discussed. Furthermore, the insights are illustrated and discussed based on a real world personnel dataset. The hybrid semi-Markov model is compared with the Markov and the semi-Markov models by diverse model selection criteria.

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Maintainability of manpower system with restricted recruitment

Cited by 2 publications

References 4 publications

Attainability for Markov and Semi-Markov Chains

Attainability for Markov and Semi-Markov Chains

Discrete Time Hybrid Semi-Markov Models in Manpower Planning

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