By Topic

(1+1) genetic algorithm fitness dynamics in a changing environment

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
S. A. Stanhope ; Artificial Intelligence Lab., Michigan Univ., Ann Arbor, MI, USA ; J. M. Daida

We analyze the fitness dynamics of a (1+1) mutation-only genetic algorithm (GA) operating on a family of simple time-dependent fitness functions. Resulting models of behavior are used in the prediction of GA performance on this fitness function. The accuracy of performance predictions are compared to actual GA runs, and results are discussed in relation to analyses of the stationary version of the dynamic fitness landscape and to prior work performed in the field of evolutionary optimization of dynamic fitness functions

Published in:

Evolutionary Computation, 1999. CEC 99. Proceedings of the 1999 Congress on  (Volume:3 )

Date of Conference:

1999