de

Description:

de

A Library for Differential Evolution Optimization
Usage #
A simple usage example:
import 'package:de/de.dart';

double f(List<double> x) {
return -(pow(x[0] - 3.14159265, 2.0) + pow(x[1] - exp(1.0), 2.0));
}

void main(){
DE de = DE(f, [-500, -500], [500, 500], cr: 0.99, F: 1.20, popsize: 300);
de.iterateN(5000);
Solution best = de.getBest();
print(best);
}
copied to clipboard
Details #

The objective function is always in the form of

double f(List<double> x){

}
copied to clipboard


The optimization is always a maximation. If the objective
function of the problem is a minimization, the returned value of the
objective function can be multiplied by -1.0.


The default parameters of the classical Differential Evolution Optimization
are set to cr = 0.8 and F = 1.0. These optimization parameters can be customized
in the constructor of DE class.