The DOI matches its Crossref record; 15 of the 15 references it cites were found in a registry or an index.
Evolutionary Algorithms, Homomorphous Mappings, and Constrained Parameter Optimization
Abstract
During the last five years, several methods have been proposed for handling nonlinear constraints using evolutionary algorithms (EAs) for numerical optimization problems. Recent survey papers classify these methods into four categories: preservation of feasibility, penalty functions, searching for feasibility, and other hybrids. In this paper we investigate a new approach for solving constrained numerical optimization problems which incorporates a homomorphous mapping between n-dimensional cube and a feasible search space. This approach constitutes an example of the fifth decoder-based category of constraint handling techniques. We demonstrate the power of this new approach on several test cases and discuss its further potential.
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Cites
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A review on genetic algorithm: past, present, and future
Katoch, S., Chauhan, S. S., & Kumar, V. (2021) · Multimedia Tools and Applications · doi:10.1007/s11042-020-10139-6 · Cited by 4,655
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Bat algorithm: a novel approach for global engineering optimization
Yang, X., & Hossein Gandomi, A. (2012) · Engineering Computations · doi:10.1108/02644401211235834 · Cited by 1,751
Constraint-handling in genetic algorithms through the use of dominance-based tournament selection
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DEPSO: hybrid particle swarm with differential evolution operator
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Metadata
- Authors
- Koziel, S., & Michalewicz, Z.
- Venue
- Evolutionary Computation
- Publisher
- MIT Press - Journals
- Published
- 1999-03
- Volume
- 7
- Issue
- 1
- Pages
- 19-44
- ISSN
- 1063-6560 (ISSN-L)
- 1530-9304
- OpenAlex
- W2038659300
- Cited by
- 758
- References
- 15
- FWCI
- 17.09
- Type
- journal article
- Language
- en
- Open access
- closed
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