OPTIMAL TRAINING POLICY FOR PROMOTION - STOCHASTIC MODELS OF MANPOWER SYSTEMS

In this paper, the optimal planning of manpower training programmes in a manpower system with two grades is discussed. The planning of manpower training within a given organization involves a trade-off between training costs and expected return. These planning problems are examined through models th...

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Main Authors: V.S.S. Yadavalli, R. Natarajan, S. Udayabhaskaran
Format: Article
Language:English
Published: Stellenbosch University 2012-01-01
Series:South African Journal of Industrial Engineering
Online Access:http://sajie.journals.ac.za/pub/article/view/315
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spelling doaj-08eab170a9fd44248209dc9eb8776abb2020-11-25T01:45:48ZengStellenbosch UniversitySouth African Journal of Industrial Engineering1012-277X2224-78902012-01-01131OPTIMAL TRAINING POLICY FOR PROMOTION - STOCHASTIC MODELS OF MANPOWER SYSTEMSV.S.S. YadavalliR. NatarajanS. UdayabhaskaranIn this paper, the optimal planning of manpower training programmes in a manpower system with two grades is discussed. The planning of manpower training within a given organization involves a trade-off between training costs and expected return. These planning problems are examined through models that reflect the random nature of manpower movement in two grades. To be specific, the system consists of two grades, grade 1 and grade 2. Any number of persons in grade 2 can be sent for training and after the completion of training, they will stay in grade 2 and will be given promotion as and when vacancies arise in grade 1. Vacancies arise in grade 1 only by wastage. A person in grade 1 can leave the system with probability p. Vacancies are filled with persons in grade 2 who have completed the training. It is assumed that there is a perfect passing rate and that the sizes of both grades are fixed. Assuming that the planning horizon is finite and is T, the underlying stochastic process is identified as a finite state Markov chain and using dynamic programming, a policy is evolved to determine how many persons should be sent for training at any time k so as to minimize the total expected cost for the entire planning period T.http://sajie.journals.ac.za/pub/article/view/315
collection DOAJ
language English
format Article
sources DOAJ
author V.S.S. Yadavalli
R. Natarajan
S. Udayabhaskaran
spellingShingle V.S.S. Yadavalli
R. Natarajan
S. Udayabhaskaran
OPTIMAL TRAINING POLICY FOR PROMOTION - STOCHASTIC MODELS OF MANPOWER SYSTEMS
South African Journal of Industrial Engineering
author_facet V.S.S. Yadavalli
R. Natarajan
S. Udayabhaskaran
author_sort V.S.S. Yadavalli
title OPTIMAL TRAINING POLICY FOR PROMOTION - STOCHASTIC MODELS OF MANPOWER SYSTEMS
title_short OPTIMAL TRAINING POLICY FOR PROMOTION - STOCHASTIC MODELS OF MANPOWER SYSTEMS
title_full OPTIMAL TRAINING POLICY FOR PROMOTION - STOCHASTIC MODELS OF MANPOWER SYSTEMS
title_fullStr OPTIMAL TRAINING POLICY FOR PROMOTION - STOCHASTIC MODELS OF MANPOWER SYSTEMS
title_full_unstemmed OPTIMAL TRAINING POLICY FOR PROMOTION - STOCHASTIC MODELS OF MANPOWER SYSTEMS
title_sort optimal training policy for promotion - stochastic models of manpower systems
publisher Stellenbosch University
series South African Journal of Industrial Engineering
issn 1012-277X
2224-7890
publishDate 2012-01-01
description In this paper, the optimal planning of manpower training programmes in a manpower system with two grades is discussed. The planning of manpower training within a given organization involves a trade-off between training costs and expected return. These planning problems are examined through models that reflect the random nature of manpower movement in two grades. To be specific, the system consists of two grades, grade 1 and grade 2. Any number of persons in grade 2 can be sent for training and after the completion of training, they will stay in grade 2 and will be given promotion as and when vacancies arise in grade 1. Vacancies arise in grade 1 only by wastage. A person in grade 1 can leave the system with probability p. Vacancies are filled with persons in grade 2 who have completed the training. It is assumed that there is a perfect passing rate and that the sizes of both grades are fixed. Assuming that the planning horizon is finite and is T, the underlying stochastic process is identified as a finite state Markov chain and using dynamic programming, a policy is evolved to determine how many persons should be sent for training at any time k so as to minimize the total expected cost for the entire planning period T.
url http://sajie.journals.ac.za/pub/article/view/315
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