Abstract
Strategies involving smoothing of the objective function have been used to help solve difficult global optimization problems arising in molecular chemistry. This paper proposes a new smoothing approach and examines some basic issues in smoothing for molecular configuration problems. We first propose a new, simple algebraic way of smoothing the Lennard-Jones energy function, which is an important component of the energy in many molecular models. This simple smoothing technique is shown to have close similarities to previously-proposed, spatial averaging smoothing techniques. We also present some experimental studies of the behavior of local and global minimizers under smoothing of the potential energy in Lennard-Jones problems. An examination of minimizer trajectories from these smoothed problems shows significant limitations in the use of smoothing to directly solve global optimization problems.
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Shao, CS., Byrd, R., Eskow, E. et al. Global Optimization For Molecular Clusters Using A New Smoothing Approach. Journal of Global Optimization 16, 167–196 (2000). https://doi.org/10.1023/A:1008387208683
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DOI: https://doi.org/10.1023/A:1008387208683