Title
|
|
|
|
The effect of spin-flip symmetry on the performance of the simple GA
| |
Author
|
|
|
|
| |
Abstract
|
|
|
|
We use the one-dimensional nearest neighbor interaction functions (NNIs) to show how the presence of symmetry in a fitness function greatly influences the convergence behavior of the simple genetic algorithm (SGA). The effect of symmetry on the SGA supports the statement that it is not the amount of interaction present in a fitness function, measured e.g. by Davidor's epistasis variance and the experimental design techniques introduced by Beeves a;nd Wright, which is important, but the kind of interaction. The NNI functions exhibit a minimal amount of second order interaction, are trivial to optimize deterministically and yet show a wide range of SGA behavior. They have been extensively studied in statistical physics; results from this field explain the negative effect of symmetry on the convergence behavior of the SGA. This note intends to introduce them to the GA-community. |
| |
Language
|
|
|
|
English
| |
Source (journal)
|
|
|
|
Lecture notes in computer science. - Berlin, 1973, currens
| |
Source (book)
|
|
|
|
5th International Conference on Parallel Problem Solving from Nature, (PPSN V), SEP 27-30, 1998, AMSTERDAM, NETHERLANDS
| |
Publication
|
|
|
|
Berlin
:
1998
| |
ISBN
|
|
|
|
3-540-65078-4
| |
Volume/pages
|
|
|
|
1498
(1998)
, p. 67-76
| |
ISI
|
|
|
|
000082774900007
| |
|