Mathematical Programming in Sample Surveys
Allocation Problems in Multivariate Sampling
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This book is based on the applications of mathematical programming techniques in multivariate sample surveys. The various multi-objective techniques namely chebyshev approximation, goal programming, lexicographic goal programming,fuzzy programming, D1-distances, E- constraint, value function and Distance-based etc., have been used to solve the multi-objective multivariate stratified sample survey problems. The non response case in multi-objective multivariate stratified sample surveys problem is also considered and the compromise allocations of samples are obtained. Allocation problems arising...
This book is based on the applications of mathematical programming techniques in multivariate sample surveys. The various multi-objective techniques namely chebyshev approximation, goal programming, lexicographic goal programming,fuzzy programming, D1-distances, E- constraint, value function and Distance-based etc., have been used to solve the multi-objective multivariate stratified sample survey problems. The non response case in multi-objective multivariate stratified sample surveys problem is also considered and the compromise allocations of samples are obtained. Allocation problems arising in sample surveys with stochastic parameters have also been discussed. The problems are solved by first deriving the deterministic equivalents and then by using a suitable convex programming algorithm. The new cut method, confidence interval and geometric programming are used to obtain the allocations in sample surveys.
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