Variance of Time to Recruitment for a Two Grade Manpower System with Independent and Non-Identically Inter – Decision Times and Correlated Wastages with Thresholds having Different Distributions
S. Sendhamizh Selvi1, S.Jenita2
1S. Sendhamizh Selvi, Assistant Professor, PG & Research Department of Mathematics, Government Arts College, Trichy-22.
2S. Jenita, Assistant Professor, PG & Research Department of Mathematics, Bishop Heber College, Trichy-17.
Manuscript received on 01 May 2019 | Revised Manuscript received on 15 May 2019 | Manuscript published on 30 May 2019 | PP: 1121-1126 | Volume-8 Issue-7, May 2019 | Retrieval Number: G6339058719/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In this paper, the problem of time to recruitment in an organization with two grades when it is subjected to loss of manpower due to the policy decisions taken by the organization is studied. As the exit of personnel is unpredictable, a recruitment policy involving two thresholds for each grade there are optional and mandatory, is suggested to enable the organization to plan its decision on recruitment. Based on shock model approach two mathematical models are constructed using the univariate policy of recruitment. Performance measures namely mean and variance of the time to recruitment are obtained for model I when (i) loss of man powers are exchangeable and constantly correlated exponential random variables (ii) inter-decision times form a sequence of independent and non-identically distributed exponential random variables and iii) optional and mandatory thresholds follows extended exponential distribution. In model II, optional and mandatory thresholds follows SCBZ property.
Keyword: Manpower Planning, Shock Models, Univariate Recruitment Policy, Extended Exponential Distribution, Hypo-exponential Distribution, SCBZ Property, Exchangeable and Constantly Correlated Exponential Random Variables.
Scope of the Article: Knowledge-based and Expert Systems.