Cat swarm optimization for the determination of strata boundaries

A stratified random sampling method is preferred for selecting varied populations with outliers. As opposed to plain sampling, increases statistical precision by reducing estimator variance. Before the estimator's variance, stratum boundary identification and data apportionment must be solved. In this study, a Neyman allocation strategy used address determination issue in mixed populations. addition evaluating CSO on two groups of people, comparison study was conducted using Kozak, GA, PSO, Delanius Hodge's approaches. Compared previous algorithms, numerical results indicate that proposed technique can select best-stratified boundaries various standard test functions.