In this work, a method to choose the best run order for a given experimental design is proposed, for the simple linear regression model with MA errors. More specifically we investigate the best run order of an uniform design when errors follow a MA(1) or a subset MA(k) process where k is a positive integer. The correlation matrix P resulting from the errors is usually difficult to obtain a good estimate. Using the change of variance function(CVF) to see the relation of the uncorrelated and the serially correlated errors. Criterion proposed by Zhou (2001), we find the best run order of the uniform design on [-1,1] to minimize the robust criterion, |CVF|. We will display the permutation of a run order after rearrangement by our method and show how the structure is decomposed into three categories to solve the problem.