Integer compromise allocation in multivariate stratified surveys

In multivariate stratified samplingmore than one characteristic are defined on every unit of the population. An optimum allocation which is optimum for one characteristic will generally be far from optimum for others. To resolve this problem, a compromise criterion is needed to work out a usable allocation. In this manuscript, a compromise criterion is discussed and integer compromise allocations are obtained by using goal programming technique. A numerical example is presented to illustrate the computational details, which reveals that the proposed criterion is suitable for working out a usable compromise allocation for multivariate stratified surveys