Theoretical Aspects of Evolutionary Computing pp 207-221 | Cite as
A Solvable Model of a Hard Optimisation Problem
Chapter
Abstract
The dynamics of a genetic algorithm (GA) on a model of a hard optimisation problem are analysed using a formalism which describes the changing fitness distribution of the GA population under ranking selection, uniform crossover, and mutation. The time to solve the optimisation problem is calculated in a closed form expression which enables the effect of the various GA parameters — population size, mutation rate, and selection scheme — to be understood.
Keywords
Fitness distribution macroscopic dynamics convergence time hard problem finite population effectsPreview
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