BCH (Bose, Chaudhuri, Hocquenghem) and QDC (Quadratic Double Circulant) codes are important classes of linear codes with many application domains. For large lengths, the true value of the minimum distances of these codes remains undetermined and therefore their error correcting capabilities are still unknown. The problem of searching codewords of lowest weight in linear codes is NP-hard problem and it is equivalent to the problem of the minimum distance research. Many methods have been used to attack this hardness such as genetic algorithms, simulated annealing, Multiple Impulse Method (MIM), Chen algorithm, Canteaut-Chabaud and Zimmermann algorithms. In a previous work, we have presented the method MIM-RSC to find the minimum weights by applying the MIM method on some Random sub codes of reduced dimensions. This reduction allows an efficient local search, but the important question here is which are the sub codes containing the lowest weights and how find them?. In general, the answer of this question isn’t evident and consequently many random sub codes should be exploited to have a great chance for taking a true minimum weight codeword. In this work, we present a new way to catch lowest weights by applying the Zimmermann algorithm on these random sub codes. This proposed scheme, Zimmermann-RSC, is validated on some BCH and QDC codes of known minimum weight and it is used to determine the minimum distance for many other codes of large lengths belonging to these families. The comparison between some competitors methods with the proposed scheme Zimmermann-RSC on many large BCH and QDC codes proves the efficiency of this latest in terms of the results quality and run time.