Parameter Optimization - Gene Expression Programming - page 326

Table 8.3
Performance and settings for the two-parameter function optimization
problem using the HZero algorithm and the GEP-PO algorithm.

HZero GEP-PO

Number of runs 100 100

Number of generations 100 1000

Population size 30 30

Function set -- + - * /

Terminal set ? ?

Random constants array length 10 10

Random constants type Rational Rational

Random constants range [0, 10] [-1, 1]

Head length 0 6

Gene length 2 20

Number of genes 2 2

Chromosome length 4 40

Mutation rate -- 0.025

Inversion rate -- 0.1

IS transposition rate -- 0.1

RIS transposition rate -- 0.1

One-point recombination rate 0.3 0.3

Two-point recombination rate 0.3 0.3

Gene recombination rate 0.3 0.3

Gene transposition rate 0.1 0.1

Random constants mutation rate 0.35 0.01

Dc-specific mutation rate 0.01 0.025

Dc-specific inversion rate -- 0.1

Dc-specific transposition rate -- 0.1

Average best-of-run output 18.5148 18.5387

Success rate 80% 93%

For instance, the following set of parameter values was discovered by the
HZero algorithm in generation 73 of run 77:

f (9.038421, 8.668366) = 18.5546969067

And the set below was designed by the GEP-PO algorithm in generation 155
of run 20:

f (9.03893887031, 8.66878467558) = 18.5547140746