Comparison of the Efficiency of the Various Algorithms in Stratified Sampling when the Initial Solutions are Determined with Geometric Method

Abstract

The main aim of this paper is to examine the efficiency of Genetic Algorithm (GA) of Keskinturk and Er (2007)[1], Kozak’s (2004) Random Search[2] and Lavallee and Hidiroglou’s (1988) Iterative Algorithm method[3] on determination of the stratum boundaries that minimize the variance of the estimate. Initial starting boundaries of the mentioned algorithms are obtained randomly. Here, it is aimed to reach better results in a shorter period of time by utilizing the initial boundaries obtained from Gunning and Horgan’s (2004) geometric method[4] compared to the random initial boundaries. Three algorithms are applied on various populations with both random and geometric initial boundaries and their performances are compared. With the stratification of 11 heterogenous populations that have different properties, higher variance of the estimates or infeasible solutions can be observed once the initial boundaries are obtained with geometric method.