Size fair and homologous tree genetic programming crossovers
William B. Langdon · 1999
Size fair and homologous crossover genetic operators for tree based genetic programming are described and tested. Both produce considerably reduced increases in program size and no detrimental effect on GP performance. GP search spaces are partitioned by the ridge in the number of program v. their size and depth. A ramped uniform random initialisation is described which straddles the ridge. With subtree crossover trees increase about one level per generation leading to sub-quadratic bloat in length. 1 INTRODUCTION It has been known for some time that programs within GP populations tend to rapidly increase in size as the population evolves. If unchecked this consumes excessive machine resources. This is usually addressed either by enforcing a size or depth limit on the programs or by an explicit size penalty in the fitness measure, although other techniques may be used. Both main approaches have problems. It has been shown that the protective effect of inviable code (which does not eff...