A novel and effective cluster similarity checking method using the connectivity table (CT) is proposed in this study. Because CT contains the topological information of a cluster, configurations at different funnels on the potential energy surface (PES) show great difference in their CTs. An adaptive immune optimization algorithm (AIOA) is utilized for optimization of Lennard-Jones (LJ) clusters up to LJ(110) using the CT for similarity checking. It is proved that the method is very efficient, and the method is also capable for optimizations of larger clusters, e.g., LJ(200). (C) 2004 Elsevier B.V. All rights reserved.