Title :
The gambler´s ruin problem, genetic algorithms, and the sizing of populations
Author :
Harik, Georges ; Cantú-Paz, Erick ; Goldberg, David E. ; Miller, Brad L.
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Michigan Univ., Ann Arbor, MI, USA
Abstract :
The paper presents a model for predicting the convergence quality of genetic algorithms. The model incorporates previous knowledge about decision making in genetic algorithms and the initial supply of building blocks in a novel way. The result is an equation that accurately predicts the quality of the solution found by a GA using a given population size. Adjustments for different selection intensities are considered and computational experiments demonstrate the effectiveness of the model
Keywords :
convergence; decision theory; genetic algorithms; probability; GA; building blocks; computational experiments; convergence quality prediction; decision making; gamblers ruin problem; genetic algorithms; population size; population sizing; previous knowledge; selection intensities; Computer science; Convergence; Decision making; Equations; Genetic algorithms; Genetic engineering; Laboratories; Predictive models;
Conference_Titel :
Evolutionary Computation, 1997., IEEE International Conference on
Conference_Location :
Indianapolis, IN
Print_ISBN :
0-7803-3949-5
DOI :
10.1109/ICEC.1997.592259
