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Evaluation of genetic algorithm concepts using model problems. part 1; single-objective optimization
| Content Provider | NASA Technical Reports Server (NTRS) |
|---|---|
| Author | Pulliam, Thomas H. Holst, Terry L. |
| Copyright Year | 2003 |
| Description | A genetic-algorithm-based optimization approach is described and evaluated using a simple hill-climbing model problem. The model problem utilized herein allows for the broad specification of a large number of search spaces including spaces with an arbitrary number of genes or decision variables and an arbitrary number hills or modes. In the present study, only single objective problems are considered. Results indicate that the genetic algorithm optimization approach is flexible in application and extremely reliable, providing optimal results for all problems attempted. The most difficult problems - those with large hyper-volumes and multi-mode search spaces containing a large number of genes - require a large number of function evaluations for GA convergence, but they always converge. |
| File Size | 1932778 |
| Page Count | 30 |
| File Format | |
| Alternate Webpage(s) | http://archive.org/details/NASA_NTRS_Archive_20030065967 |
| Archival Resource Key | ark:/13960/t54f6r71w |
| Language | English |
| Publisher Date | 2003-05-22 |
| Access Restriction | Open |
| Subject Keyword | Numerical Analysis Problems Variable Decisions Models Genetic Algorithms Aerospace Engineering Design Optimization Ntrs Nasa Technical Reports Server (ntrs) Nasa Technical Reports Server Aerodynamics Aircraft Aerospace Aeronautic Space Science |
| Content Type | Text |
| Resource Type | Technical Report |
