Estimation of finite population mean in multivariate stratified sampling under cost function using goal programming

In practical utilization of stratified random sampling scheme,the investigator meets a problem to select a sample that maximizes the precision of a finite populationmean under cost constraint. an allocation of sample size becomes complicated whenmore than one characteristic is observed fromeach selected unit in a sample. inmany real life situations,a linear cost function of a sample size nh 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. copyright © 2014 atta ullah et al.