A filter-based evolutionary algorithm for constrained optimization.

Journal Article · Sun Feb 01 00:00:00 EST 2004 · Proposed for publication in Evolutionary Computations.

OSTI ID:971830

Clevenger, Lauren M ^[1]; Hart, William Eugene; Ferguson, Lauren Ann ^[2]

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1. University of New Mexico
2. Texas Tech University

We introduce a filter-based evolutionary algorithm (FEA) for constrained optimization. The filter used by an FEA explicitly imposes the concept of dominance on a partially ordered solution set. We show that the algorithm is provably robust for both linear and nonlinear problems and constraints. FEAs use a finite pattern of mutation offsets, and our analysis is closely related to recent convergence results for pattern search methods. We discuss how properties of this pattern impact the ability of an FEA to converge to a constrained local optimum.

• Research Organization: Sandia National Laboratories (SNL), Albuquerque, NM, and Livermore, CA (United States)
• Sponsoring Organization: USDOE
• DOE Contract Number: AC04-94AL85000
• OSTI ID: 971830
• Report Number(s): SAND2005-2823J; TRN: US201004%%218
• Journal Information: Proposed for publication in Evolutionary Computations., Journal Name: Proposed for publication in Evolutionary Computations.
• Country of Publication: United States
• Language: English

Related Subjects

97 MATHEMATICAL METHODS AND COMPUTING
99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE
ALGORITHMS
CONVERGENCE
NONLINEAR PROBLEMS
OPTIMIZATION
PATTERN RECOGNITION