THE USE OF MULTI-ABSORBING STATES MARKOV CHAIN IN THE ANALYSIS OF NON-HOMOGENEOUS MARKOV FUZZY MANPOWER SYSTEM
DOI:
https://doi.org/10.60787/tnamp.v22.565Keywords:
Fuzzy Partitioning, Membership Function, Fuzzy States, Multi-Absorbing States Markov ChainAbstract
There are many studies in literature that took into consideration intra-state heterogeneity concerning individual transition behavior due to latent factors. However, none of these studies in literature has captured any specific or combination of specific latent factors responsible for differences in transition behavior within a homogeneous group in manpower model. Also, no work in literature has been able to unbundle successfully retired staff in a nonhomogeneous Markov fuzzy manpower model. In this study, we considered a hierarchically graded Markov manpower system where promotion of employees is based on the innovativeness and job performance capability levels of the personnel. In this study, the model is proposed to deal with problem of vagueness involved in gradual transition of members from one grade to another in a manpower system. The model is also proposed to incorporate key personality traits that influence employees belonging to a homogeneous group to behave differently. This study also seeks to unbundle successfully retired staff in nonhomogeneous Markov fuzzy manpower system using multi-absorbing states Markov chain. The mean time to absorption and long run absorption rates in each fuzzy state were obtained
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