NDLI: Evaluation of genetic algorithm concepts using model problems. part 2; multi-objective optimization

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Evaluation of genetic algorithm concepts using model problems. part 2; multi-objective optimization

Content Provider	NASA Technical Reports Server (NTRS)
Author	Pulliam, Thomas H. Holst, Terry L.
Copyright Year	2003
Description	A genetic algorithm approach suitable for solving multi-objective optimization problems is described and evaluated using a series of simple model problems. Several new features including 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. Results indicate that the genetic algorithm optimization approach is flexible in application and extremely reliable, providing optimal results for all optimization problems attempted. The binning algorithm generally provides pareto front quality enhancements and moderate convergence efficiency improvements for most of the model problems. The gene-space transformation procedure provides a large convergence efficiency enhancement for problems with non-convoluted pareto fronts and a degradation in efficiency for problems with convoluted pareto fronts. The most difficult problems --multi-mode search spaces with a large number of genes and convoluted pareto fronts-- require a large number of function evaluations for GA convergence, but always converge.
File Size	1532986
Page Count	44
File Format	PDF
Alternate Webpage(s)	http://archive.org/details/NASA_NTRS_Archive_20040031786
Archival Resource Key	ark:/13960/t0gv0js15
Language	English
Publisher Date	2003-12-01
Access Restriction	Open
Subject Keyword	Mathematical And Computer Sciences (general) Operators Mathematics Vector Analysis Stochastic Processes Mathematical Models Optimization Genetic Algorithms Convergence 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

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