Dominant takeover regimes for genetic algorithms

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

FY 1995 Scientific and Technical Reports, Articles, Papers, and Presentations, Volume 1

This document presents formal NASA technical reports, papers published in technical journals, and presentations by MSFC personnel in FY95. It also includes papers of MSFC contractors. The information in this report may be of value to the scientific and engineering community in determining what information has been published and what is available