The problem of identifying protein complexes is of great significance for studying the protein mechanisms in different cellular systems. It is for this reason that many computational approaches have been proposed to solve the problem. Yet few of them have endeavored to discover overlapping protein complexes, which are crucial to improve the accuracy performance. Hence, in this paper, we explore the feasibility of making use of a fuzzy clustering approach to identify overlapping protein complexes in a natural manner. To do so, we first formulate the identification problem as an optimization problem by following certain intuitions and then develop an algorithm to solve it so that the memberships of each protein to different protein complexes can be optimized to eventually infer the protein complexes of interest. The experimental results on several yeast protein interaction networks show that our algorithm is promising in terms of accuracy.