A STUDY OF GENETIC ALGORITHM APPROACHES TO GLOBAL GEOMETRY OPTIMIZATION OF AROMATIC HYDROCARBON MICROCLUSTERS

We have carried out potential energy minimization calculations on benz ene, naphthalene, and anthracene clusters using model potential energy functions. The primary purpose was to examine several techniques whic h use concepts from the field of genetic algorithms (GA). In particula r, we compared the ''traditional GA'' in which the variables of the pr oblem are coded into binary and genetic operations performed on these, and recent methods which use real-valued variables. Our primary techn ique, the ''space-fixed modified GA'' (SFMGA), also uses a conjugate g radient descent on the geometries generated by the GA. Our results sho w the convergence to the global minimum is greatly improved by the use of the descent minimization. In fact, it appears unlikely that the tr aditional GA's are useful for any but the very simplest clusters. We h ave also compared the SFMGA with simulated annealing (SA) and Wales an d Doye's recent basin-hopping (BH) technique. We find our method to be superior to SA, and comparable to BH. (C) 1998 American Institute of Physics.