An Application of Stochastic Programming with Weibull Distribution-Cluster Based Optimum Allocation of Recruitment in Manpower Planning

M. Jeeva; Rajalakshmi Rajagopal; V. Charles; V. S.S. Yadavalli

doi:10.1081/SAP-120030457

An Application of Stochastic Programming with Weibull Distribution-Cluster Based Optimum Allocation of Recruitment in Manpower Planning

M. Jeeva
, Rajalakshmi Rajagopal
, V. Charles
, V. S.S. Yadavalli

Ethiraj College For Women
Loyola College, Chennai
National Institute of Technology, Warangal
University of Pretoria

Research output: Contribution to journal › Article › peer-review

9 Scopus citations

Abstract

Recruitment of persons for various assignments with required talents in an organization is an important feature, since it plays a vital role in the growth of the organization. To achieve the required expertise in recruitment, in this paper Linear Stochastic Programming (LSP) is applied along with cluster analysis technique. The aim of this paper is to obtain an optimal allocation of persons to different jobs, so that the time taken to complete all the jobs is minimum. The time taken for a person to complete a job is assumed to follow Weibull distribution. The parameters of Weibull distribution is obtained through Maximum Likelihood Estimator (MLE) approach, along with Cohen's iterative process.

Original language	English
Pages (from-to)	801-812
Number of pages	12
Journal	Stochastic Analysis and Applications
Volume	22
Issue number	3
DOIs	https://doi.org/10.1081/SAP-120030457
State	Published - May 2004
Externally published	Yes

Keywords

Cluster analysis
Linear stochastic programming
Maximum likelihood estimators
Nonlinear probabilistic constraints
Sequential programming
Weibull distribution

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10.1081/SAP-120030457

Cite this

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title = "An Application of Stochastic Programming with Weibull Distribution-Cluster Based Optimum Allocation of Recruitment in Manpower Planning",

abstract = "Recruitment of persons for various assignments with required talents in an organization is an important feature, since it plays a vital role in the growth of the organization. To achieve the required expertise in recruitment, in this paper Linear Stochastic Programming (LSP) is applied along with cluster analysis technique. The aim of this paper is to obtain an optimal allocation of persons to different jobs, so that the time taken to complete all the jobs is minimum. The time taken for a person to complete a job is assumed to follow Weibull distribution. The parameters of Weibull distribution is obtained through Maximum Likelihood Estimator (MLE) approach, along with Cohen's iterative process.",

keywords = "Cluster analysis, Linear stochastic programming, Maximum likelihood estimators, Nonlinear probabilistic constraints, Sequential programming, Weibull distribution",

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AU - Rajagopal, Rajalakshmi

AU - Charles, V.

AU - Yadavalli, V. S.S.

PY - 2004/5

Y1 - 2004/5

N2 - Recruitment of persons for various assignments with required talents in an organization is an important feature, since it plays a vital role in the growth of the organization. To achieve the required expertise in recruitment, in this paper Linear Stochastic Programming (LSP) is applied along with cluster analysis technique. The aim of this paper is to obtain an optimal allocation of persons to different jobs, so that the time taken to complete all the jobs is minimum. The time taken for a person to complete a job is assumed to follow Weibull distribution. The parameters of Weibull distribution is obtained through Maximum Likelihood Estimator (MLE) approach, along with Cohen's iterative process.

AB - Recruitment of persons for various assignments with required talents in an organization is an important feature, since it plays a vital role in the growth of the organization. To achieve the required expertise in recruitment, in this paper Linear Stochastic Programming (LSP) is applied along with cluster analysis technique. The aim of this paper is to obtain an optimal allocation of persons to different jobs, so that the time taken to complete all the jobs is minimum. The time taken for a person to complete a job is assumed to follow Weibull distribution. The parameters of Weibull distribution is obtained through Maximum Likelihood Estimator (MLE) approach, along with Cohen's iterative process.

KW - Cluster analysis

KW - Linear stochastic programming

KW - Maximum likelihood estimators

KW - Nonlinear probabilistic constraints

KW - Sequential programming

KW - Weibull distribution

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DO - 10.1081/SAP-120030457

M3 - Article

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SN - 0736-2994

VL - 22

SP - 801

EP - 812

JO - Stochastic Analysis and Applications

JF - Stochastic Analysis and Applications

IS - 3

ER -

An Application of Stochastic Programming with Weibull Distribution-Cluster Based Optimum Allocation of Recruitment in Manpower Planning

Abstract

Keywords

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