The article introduces a new method called Genetic algorithm for improving linear regression models when errors are not consistent. This technique helps estimate parameters accurately even when the errors vary in size. By using Genetic algorithm, researchers can find the best parameters for their models without needing to know the exact pattern of error variation. This approach was tested on a dataset and showed promising results in estimating regression parameters and variance.