On the limited memory BFGS method for large scale optimization
Mathematical Programming: Series A and B
Fast Global Optimization of Difficult Lennard-Jones Clusters
Computational Optimization and Applications
Global Optima of Lennard-Jones Clusters
Journal of Global Optimization
Global Optimization on Funneling Landscapes
Journal of Global Optimization
Docking of Atomic Clusters Through Nonlinear Optimization
Journal of Global Optimization
On the multilevel structure of global optimization problems
Computational Optimization and Applications
Global Optimization of Morse Clusters by Potential Energy Transformations
INFORMS Journal on Computing
New results for molecular formation under pairwise potential minimization
Computational Optimization and Applications
Solving molecular distance geometry problems by global optimization algorithms
Computational Optimization and Applications
Global optimization of binary Lennard-Jones clusters
Optimization Methods & Software - GLOBAL OPTIMIZATION
A nested heuristic for parameter tuning in Support Vector Machines
Computers and Operations Research
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A stochastic global optimization method is applied to the challenging problem of finding the minimum energy conformation of a cluster of identical atoms interacting through the Lennard-Jones potential. The method proposed incorporates within an already existing and quite successful method, monotonic basin hopping, a two-phase local search procedure which is capable of significantly enlarging the basin of attraction of the global optimum. The experiments reported confirm the considerable advantages of this approach, in particular for all those cases which are considered in the literature as the most challenging ones, namely 75, 98, 102 atoms. While being capable of discovering all putative global optima in the range considered, the method proposed improves by more than two orders of magnitude the speed and the percentage of success in finding the global optima of clusters of 75, 98, 102 atoms.