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);
}

Details

• The objective function is always in the form of

double f(List<double> x){

}

• 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.