Linkage learning, overlapping building blocks, and systematic strategy for scalable recombination
Journal
GECCO 2005 - Genetic and Evolutionary Computation Conference
Pages
1217-1224
Date Issued
2005
Author(s)
Abstract
This paper aims at an important, but poorly studied area in genetic algorithm (GA) field: How to design the crossover operator for problems with overlapping building blocks (BBs). To investigate this issue systematically, the relationship between an inaccurate linkage model and the convergence time of GA is studied. Specifically, the effect of the error of so-called false linkage is analogized to a lower exchange probability of uniform crossover. The derived qualitative convergence-time model is used to develop a scalable recombination strategy for problems with overlapping BBs. A set of problems with circularly overlapping BBs exemplify the recombination strategy.
SDGs
Type
conference paper