Title :
An experimental study of benchmarking functions for genetic algorithms
Author :
Digalakis, Jason G. ; Margaritis, Konstantinos G.
Author_Institution :
Dept. of Appl. Inf., Macedonia Univ., Thessaloniki, Greece
Abstract :
This paper presents a review and experimental results of major benchmarking functions used for the performance control of genetic algorithms (GAs). Parameters considered include the effect of population size, crossover probability and pseudo-random number generators. The general computational behavior of two basic GAs models, the Generational Replacement Model and the Steady State Replacement Model is evaluated
Keywords :
algorithm theory; genetic algorithms; Generational Replacement Model; ISAAC; Steady State Replacement Model; benchmarking functions; crossover probability; genetic algorithms; performance control; population size; pseudo-random number generators; Algorithm design and analysis; Benchmark testing; Biological system modeling; Biological systems; Costs; Genetic algorithms; Informatics; Performance analysis; Steady-state; Telephony;
Conference_Titel :
Systems, Man, and Cybernetics, 2000 IEEE International Conference on
Conference_Location :
Nashville, TN
Print_ISBN :
0-7803-6583-6
DOI :
10.1109/ICSMC.2000.886604
