In this paper, a vigorous attempt has been made to study Hopfield neural network for storing and later recalling of random patterns using conventional hebbian learning rule and genetic algorithm. Storing of these patterns in the network is done using Hebbian learning rule followed by recalling of these patterns on presentation of distorted input patterns is done using both the methods i.e. Hebbian rule and genetic algorithm. The optimal weight matrix obtained is used to generate new weight matrices for the efficient recalling of prototype input patterns. Performance evaluation of the network is done on the basis of pattern recall with maximum noise present in patterns. The results thus obtained shows that the recall of these random patterns is more successful by using genetic algorithm.