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Thesis Name: Global geometry optimization of Na+(H2O)m clusters using a hybrid algorithm
Usage: A hybrid algorithm
Keyword: Hybrid optimization algorithm, potential function, Na+(H2O)m clusters
Remarks: Many recent developments in the computational technology for random search have been made in the area of atomic and molecular cluster calculations. For example, Niesse used a modified GA method to optimize the geometry of atomic and molecular clusters[1]. Greguick proposed a modified deterministic/stochastic GA method for the determination of the global minimum of (Ar)n and B(Ar)n clusters. The deterministic / stochastic GA converged more quickly to the global minimum than other random search procedures[2]. As a global optimization algorithm, the simulated annealing algorithm has been widely used to optimize the molecular clusters too[3]. But, applying all these methods to larger systems is limited. To make the random search more efficient, based on GA, FSA and CGA we have presented a hybrid optimization algorithm and applied it to water clusters in the previous works. The results showed the structures of water clusters with lower potential energy were found and a more quick optimization strategy than using other was got. So, this method is proved more effective and it can be used to optimize the structure of water clusters in the electrostatic field of sodium ion in this paper.
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