Illinois Genetic Algorithms Laboratory

Sastry, K., and Goldberg, D. E. (2002)
TR No.: 2002002 | Download PDF | Download PS

Abstract:
This study investigates the decision making between fitness function with
differing variance and computational-cost values. The objective of this
decision making is to provide evaluation relaxation and thus enhance the
efficiency of the genetic search. A decision-making strategy has been
developed to maximize speed-up using facetwise models for the convergence
time and population sizing. Results indicate that using this decision
making, significant speed-up can be obtained.