An Analysis of Dynamic Mutation Operators for Conformational Sampling

A comparison analysis of dynamic mutation operators is proposed, having the conformational sampling problem as a case study. The analysis is sustained by a parallel Optimal Computing Budget Allocation (OCBA) selection procedure, employed in order to attain computational speedup. A Pearson system distribution based mutation operator is proposed, allowing for a highly flexible construction. As defined by a set of four parameters, the mean, variance, skewness and kurtosis, a large number of distributions can be simulated. As determined by the analysis outcomes, the class of operators exhibiting significant energy minimization or Root Mean Square Deviation (RMSD) bias is identified. Experiments are carried out on a large number of computational resources, allowing for the outline of an automatic a priori operator tuning and selection methodology. Although not presented in this chapter, similar complementary studies have been conducted on intensification operators and local search algorithms.

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