Please use this identifier to cite or link to this item: http://hdl.handle.net/10311/1891
Title: Manpower systems operating under heavy and light tailed inter-exit time distributions
Authors: Sivasamy, R.
Rao, P. Tirupathi
Thaga, K.
Keywords: Manpower system
recruitment policy
inter-exit time
wastage
waiting time to breakdown
heavy tailed inter-exit time distribution and light tailed distribution
Issue Date: 2014
Publisher: Scientific Research, www.scirp.org/
Citation: Sivasamy, R., Rao, P.T. & Thaga, K. (2014) Manpower systems operating under heavy and light tailed inter-exit time distributions. Applied Mathematics, Vol. 5, pp. 285-291
Abstract: This paper considers a Manpower system where “exits” of employed personnel produce some wastage or loss. This system monitors these wastages over the sequence of exit epochs {t0 = 0 and tk; k = 1, 2,∙∙∙} that form a re- current process and admit recruitment when the cumulative loss of man hours crosses a threshold level Y, which is also called the breakdown level. It is assumed that the inter-exit times Tk = tk−1 − tk, k = 1, 2,∙∙∙ are independent and identically distributed random variables with a common cumulative distribution function (CDF) B(t) = P(Tk < t) which has a tail 1 – B(t) behaving like t−v with 1 < v < 2 as t → ∞. The amounts {Xk} of wastages incurred during these inter-exit times {Tk} are independent and identically distributed random variables with CDF P(Xk < X) = G(x) and Y is distributed, independently of {Xk} and {tk}, as an exponentiated exponential law with CDF H(y) = P(Y < y) = (1 − e−λy)n. The mean waiting time to break down of the system has been obtained assuming B(t) to be heavy tailed and as well as light tailed. For the exponential case of G(x), a comparative study has also been made between heavy tailed mean waiting time to break down and light tailed mean waiting time to break down values. The recruitment policy operating under the heavy tailed case is shown to be more economical in all types of man- power systems.
URI: http://hdl.handle.net/10311/1891
ISSN: 2152-7385
Appears in Collections:Research articles (Dept of Statistics)

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