In the source localization problem, time differences of arrival (TDOA) and intensity level differences (ILD) of microphones can be employed to estimate the source location. Due to existing additive noise in real applications the ILD measurement provides less reliable information compared to the TDOA. Therefore, this study is focused on developing algorithms employing the TDOA information only. In the past studies, TDOA were used mostly for estimation of direction of the arrival (DOA) parameter. To find the source location from TDOA of different microphones, the intersection of several equations must be calculated which this solving process requires complex numerical analysis. The solving processes, which generally ignore the noise existence, are not robust to noise and might not converge to the true answer in real-world applications. This paper tackles the source localization problem by converting the numerical analysis approach to an iterative minimization one in order to improve localization accuracy in noisy conditions. The performance of the proposed iterative minimization algorithm is seen to be sensitive to the initial values. To address this issue, another algorithm, based on Euclidean Distance theory, is developed to obtain stable and accurate results. The proposed framework works properly in different SNR conditions. The results show that the proposed methods are more accurate than the existing numerical analysis based methods in different noisy conditions even in very low SNR conditions.