Online Optfinder - Genetic Algorithms Simulations

genetic algorithms, genetic populations, computer simulations, optfinder, free, online learning, free online learning, taketechease, ilona kosinska, kosinska

Function To Optimization (Fitness Function)

Type of search: one-parametric.

Set number of variables

Variable's range (the same for each)

Set minimum value of a variable

Set maximum value of a variable

Write your function (use variable name: x0, x1 etc)

help

Set kind of optimum (min or max)

min
max

Population of Chromosomes

Set model of a chromosome

haploid
diploid

Set length of a chromosome

Set number of chromosomes (population size)

Set number of generations

Set probability of crossover

Set probability of mutation

Fitness Function Scaling

Set type of fitness function scaling

none
linear
sigma
power

Set multiplier (if your choice is not ,,none'')

Selection Model

Set type of selection

roulette modified roulette deterministic
random type I random type II Wetzel's rang

THIS PART IS DURING PREPARATION!!

Sharing Model

Set type of sharing function

none
phenotype
genotype

Set sharing power (if your choice is not ,,none'')

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