Comparing Evolutionary Programs and Evolutionary Pattern Search Algorithms: A Drug Docking Application
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.
- Research Organization:
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Sandia National Lab. (SNL-CA), Livermore, CA (United States)
- Sponsoring Organization:
- US Department of Energy (US)
- DOE Contract Number:
- AC04-94AL85000
- OSTI ID:
- 3571
- Report Number(s):
- SAND99-0350C; TRN: AH200112%%487
- Resource Relation:
- Conference: Genetic and Evolutionary Computation Conference, Orlando, FL (US), 07/13/1999--07/17/1999; Other Information: PBD: 10 Feb 1999
- Country of Publication:
- United States
- Language:
- English
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