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Comparing evolutionary programs and evolutionary pattern search algorithms: a drug docking application

机译:比较进化程序和进化模式搜索算法:药物对接应用

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Evolutionary programs (EPs) and evolutionary pattern search algorithms (EPSAs) are two general classes of evolutionary methods for optimizing on continuous domains. The relative performance of these methods has been evaluated on standard global optimization test functions, and these results suggest that EPSAs more robustly converge to near-optimal solutions than EPs. In this paper we evaluate the relative performance of EPSAs and EPs on a real-world application: flexible ligand binding in the Autodock docking software. We compare the performance of these methods on a suite of docking test problems. Our results confirm that EPSAs and EPs have comparable performance, and they suggest that EPSAs may be more robust on larger, more complex problems.
机译:进化程序(EPs)和进化模式搜索算法(EPSA)是用于在连续域上进行优化的两大类进化方法。这些方法的相对性能已经在标准的全局优化测试功能上进行了评估,这些结果表明,EPSA比EP更加稳健地收敛到接近最佳的解决方案。在本文中,我们评估了在实际应用中EPSA和EP的相对性能:Autodock对接软件中的柔性配体结合。我们在一系列对接测试问题上比较了这些方法的性能。我们的结果证实EPSA和EP具有可比的性能,并且它们表明EPSA在更大,更复杂的问题上可能更强大。

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