Community structure is one of the most important properties in social networks, and has received an enormous amount of attention in recent years. Community Detection, a form of clustering, is a technique which is used for the discovery of the naturally occurring associations between vertices in a given network. Initially, algorithms were developed with the intention of detecting communities in static networks. This slowly evolved into detecting communities in dynamic environments as the nature of the network itself, in general, is dynamic. Community detection in dynamic networks with better performance and better accuracy is a problem for which the authors have proposed an idea involving the combination of two techniques: local community measurement of multi resolution applied in multi – objective immune algorithm, replacing the current local search strategy. Also, this proposal is phase one of the algorithm as the second phase is still under work, without which the complete solution cannot be resolved.