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Genetic algorithms applied to multi-objective aerodynamic shape optimization (Document No: 20060014577)
| Content Provider | NASA Technical Reports Server (NTRS) |
|---|---|
| Author | Holst, Terry L. |
| Copyright Year | 2005 |
| Description | A genetic algorithm approach suitable for solving multi-objective problems is described and evaluated using a series of aerodynamic shape optimization problems. Several new features including two variations of a binning selection algorithm and a gene-space transformation procedure are included. The genetic algorithm is suitable for finding Pareto optimal solutions in search spaces that are defined by any number of genes and that contain any number of local extrema. A new masking array capability is included allowing any gene or gene subset to be eliminated as decision variables from the design space. This allows determination of the effect of a single gene or gene subset on the Pareto optimal solution. Results indicate that the genetic algorithm optimization approach is flexible in application and reliable. The binning selection algorithms generally provide Pareto front quality enhancements and moderate convergence efficiency improvements for most of the problems solved. |
| File Size | 11044537 |
| Page Count | 46 |
| File Format | |
| Alternate Webpage(s) | http://archive.org/details/NASA_NTRS_Archive_20060014577 |
| Archival Resource Key | ark:/13960/t44r2vq1q |
| Language | English |
| Publisher Date | 2005-02-01 |
| Access Restriction | Open |
| Subject Keyword | Mathematical And Computer Sciences (general) Augmentation Range Extremes Masking Aerodynamic Configurations Shape Optimization Genetic Algorithms Ntrs Nasa Technical Reports Server (ntrs) Nasa Technical Reports Server Aerodynamics Aircraft Aerospace Engineering Aerospace Aeronautic Space Science |
| Content Type | Text |
| Resource Type | Technical Report |
