The success of CALYPSO method is on account of the integration of several major techniques:

1. Structural evolution through PSO algorithm. PsO is best-known for its ability to conquer largebarriers of energy landscapes by making use of the swarm intelligence and by self-improvingstructures. Both global and local PSO algorithms have been implemented. The global Pso hasthe advantage of fast convergence, while local PSO is good at avoiding premature convergenceand thus enhance the capability of CALYPSO in dealing with more complex systems.

2. Symmetry constraints during structure generation to reduce searching space and enhance thestructural diversity.

3. Structural characterization techniques to eliminate similar structures, define nonflying areasenhance searching effciency, and divide energy surfaces for local PSO searching.

(i)bond characterization matrix technique

(ii)atom-centered symmetrical function technique

4. Introducing new structures per generation with controllable percentage to enhance structuradiversity.

5. Interface to a number of local structural optimization codes varying from highly accurate DFlmethods to fast semiempirical approaches that can deal with large systems. Local structuraoptimization enables the reduction of noise of energy surfaces and the generation of physicalljustified structures.