Estimation of Finite Population Mean in Multivariate Stratified Sampling under Cost Function Using Goal Programming. (14th August 2014)

• Record Type: Journal Article
• Authors: Ullah, Atta; Shabbir, Javid; Hussain, Zawar; Al-Zahrani, Bander
• Other Names: Wang Dongqing Academic Editor.
• Is Part Of: Journal of applied mathematics. Volume 2014(2014)
• Publication Date: 2014-08-14
• Subjects: Mathematics -- Periodicals; 519.05
• DOI: 10.1155/2014/686579
• Languages: English
• ISSNs: 1110-757X

Abstract

Abstract : In practical utilization of stratified random sampling scheme, the investigator meets a problem to select a sample that maximizes the precision of a finite population mean under cost constraint. An allocation of sample size becomes complicated when more than one characteristic is observed from each selected unit in a sample. In many real life situations, a linear cost function of a sample size n h is not a good approximation to actual cost of sample survey when traveling cost between selected units in a stratum is significant. In this paper, sample allocation problem in multivariate stratified random sampling with proposed cost function is formulated in integer nonlinear multiobjective mathematical programming. A solution procedure is proposed using extended lexicographic goal programming approach. A numerical example is presented to illustrate the computational details and to compare the efficiency of proposed compromise allocation.