Package jline.opt.solver.de

Class DifferentialEvolution

java.lang.Object

jline.opt.solver.de.DifferentialEvolution

public class DifferentialEvolution
extends Object

Self-contained port of scipy's differential_evolution that reproduces its trajectory bit-for-bit for a given integer seed, using NumpyRandomState for all draws.

Covers the configuration used by line-opt: the binomial strategies (default best1bin), updating='immediate', dithered mutation, latinhypercube initialization, polish=false, workers=1, and penalty-based constraints handled inside the objective (no scipy-level constraints). The exact numpy draw order is preserved: LHS init (uniform grid then per-column permutation), a per-generation dither uniform, and per candidate randint (fill point), shuffle (sample selection) and uniform (crossover), plus a data-dependent uniform in the bound-repair step.

Java 8 compatible.

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
static interface	DifferentialEvolution.Callback	Per-generation callback; return true to stop early.
static interface	DifferentialEvolution.Objective	Objective returning the (penalized) energy; may be +inf.
static class	DifferentialEvolution.Result

Constructor Summary

Constructors

Constructor	Description
DifferentialEvolution(DifferentialEvolution.Objective objective, double[] low, double[] high, String strategy, int popsizeMult, int maxiter, double ditherLow, double ditherHigh, double recombination, double tol, long seed)

Method Summary

Modifier and Type	Method	Description
NumpyRandomState	getRng()
void	setCallback(DifferentialEvolution.Callback cb)
DifferentialEvolution.Result	solve()

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Details

DifferentialEvolution

public DifferentialEvolution(DifferentialEvolution.Objective objective,
 double[] low,
 double[] high,
 String strategy,
 int popsizeMult,
 int maxiter,
 double ditherLow,
 double ditherHigh,
 double recombination,
 double tol,
 long seed)

Method Details

setCallback

public void setCallback(DifferentialEvolution.Callback cb)

getRng

public NumpyRandomState getRng()

solve

public DifferentialEvolution.Result solve()