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Dominant takeover regimes for genetic algorithms
| Content Provider | NASA Technical Reports Server (NTRS) |
|---|---|
| Author | Baskaran, Subbiah Noever, David |
| Copyright Year | 1995 |
| Description | The genetic algorithm (GA) is a machine-based optimization routine which connects evolutionary learning to natural genetic laws. The present work addresses the problem of obtaining the dominant takeover regimes in the GA dynamics. Estimated GA run times are computed for slow and fast convergence in the limits of high and low fitness ratios. Using Euler's device for obtaining partial sums in closed forms, the result relaxes the previously held requirements for long time limits. Analytical solution reveal that appropriately accelerated regimes can mark the ascendancy of the most fit solution. In virtually all cases, the weak (logarithmic) dependence of convergence time on problem size demonstrates the potential for the GA to solve large N-P complete problems. |
| File Size | 338567 |
| Page Count | 4 |
| File Format | |
| Alternate Webpage(s) | http://archive.org/details/NASA_NTRS_Archive_19960016398 |
| Archival Resource Key | ark:/13960/t7sn5440r |
| Language | English |
| Publisher Date | 1995-01-01 |
| Access Restriction | Open |
| Subject Keyword | Numerical Analysis Ratios Estimating Genetics Mathematical Models Run Time Computers Optimization Genetic Algorithms Fitness Convergence Sums Ntrs Nasa Technical Reports Server (ntrs) Nasa Technical Reports Server Aerodynamics Aircraft Aerospace Engineering Aerospace Aeronautic Space Science |
| Content Type | Text |
| Resource Type | Article |
