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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Genetic Algorithms Applied to Multi-Objective Aerodynamic Shape Optimization

Genetic Algorithms Applied to Multi-Objective Aerodynamic Shape Optimization

Holst, Terry L.
Nasa Technical Reports Server (Ntrs)

Paperback

General Political Science

ISBN10: 1287245412
ISBN13: 9781287245414
Publisher: Bibliogov
Published: Jul 23 2013
Pages: 50
Weight: 0.24
Height: 0.10 Width: 7.44 Depth: 9.69
Language: English
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.

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