Genetic Invariance: A New Paradigm for Genetic Algorithm Design

Joseph Culberson

Date: June 1992

University of Alberta Technical Report TR92-02

Abstract

This paper presents some experimental results and analyses of the gene invariant genetic algorithm(GIGA). Although a subclass of the class of genetic algorithms, this algorithm and its variations represent a unique approach with many interesting results. The primary distinguishing feature is that when a pair of offspring are created and chosen as worthy of membership in the population they replace their parents. With no mutation this has the effect of maintaining the original genetic material over time, although it is reorganized.

In this paper no mutation is allowed. The only genetic operator used is crossover. Several crossover operators are experimented with and analyzed. The notion of a family is introduced and different selection methods are analyzed.

Tests using simple functions, the De Jong five function test suite and several deceptive functions are reported. GIGA performs as well as traditional GAs, and sometimes better. The evidence indicates that this method makes more effective use of the crossover operator, in part because it never loses genetic material and thus has greater scope for recombination.

A new view of crossover search space structures and approaches to analysis are presented. Traditional methods of analysis for GAs do not seem to apply since GIGAs cannot be said to give increased trials to the best schemata in the usual sense. However, the analysis of crossover search space structures may have applications in traditional GA analysis.

Keywords: genetic algorithms, gene invariance, deception analysis, simulation, crossover analysis

Full Paper

It can also be retrieved by anonymous ftp ftp.cs.ualberta.ca pub/TechReports

See also:

GIGA Program Description and Operation
Joseph Culberson; June 1992 Technical Report TR92-06
Genetic Invariance: A New Approach to Genetic Algorithms
Michael Lewchuk, Master's Thesis; April 1992. Available as Technical Report TR92-05
Queries: email joe@cs.ualberta.ca

Joseph Culberson