Abstract
Energy minimization studies were carried out for a number of Cu clusters using binary and Gray-coded genetic algorithms along with real coded differential evolution, and their optimized ground state geometries are presented. The potential energy function is constructed using a two-body interaction methodology, involving both attractive and repulsive pair-potential terms. The results obtained through the evolutionary algorithms are compared against those obtained earlier using a Monte Carlo technique.
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