mljs
ml-direct
Direct - DIviding RECTangles algorithm.
The algorithm is intended to minimize real valued multivariate scalar fields over a hyper-rectangular region of N, theoretically the only prerequisite to achieve convergence is that the function must be continuous in the domain or at least continuous over a neighborhood of the global minimum.
Advanced example
import direct from 'ml-direct';
const options = {
iterations: 50,
};
const lowerBoundaries = [-1, -1.5];
const upperBoundaries = [2, 6];
const predicted = direct(griewank, lowerBoundaries, upperBoundaries, options);
function griewank(x) {
let d = x.length;
let s = 0;
let p = 1;
for (let i = 0; i < d; i++) {
s += Math.pow(x[i], 2) / Math.sqrt(4000);
p *= Math.cos(x[i] / Math.sqrt(i + 1));
}
let result = s - p + 1;
return result;
}
// predicted.minFunctionValue = 0;
// predicted.optima[0] = [0, 0]; This are the points where the function has minimum value
A tool for global optimization of real valued functions .
Installation
$ npm i ml-direct
Usage
import direct from 'ml-direct';
const options = {
iterations: 25,
};
// for x we explore values between -5 and 4
// for y we explore values between -2 and 3
const lowerBoundaries = [-5, -2];
const upperBoundaries = [4, 3];
const quadratic = function (parameters) {
let [x, y] = parameters;
return Math.pow(x, 2) + Math.pow(y, 2);
};
const predicted = direct(quadratic, lowerBoundaries, upperBoundaries, options);
// predicted.minFunctionValue = 0;
// predicted.optima[0] = [0, 0];API Documentation
References
Jones, D. R., Perttunen, C. D., & Stuckman, B. E. (1993). Lipschitzian optimization without the Lipschitz constant. Journal of optimization Theory and Applications, 79(1), 157-181.
Björkman, M., & Holmström, K. (1999). Global optimization using the DIRECT algorithm in Matlab.
Preparata, F. P., & Shamos, M. I. (2012). Computational geometry: an introduction. Springer Science & Business Media.