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further refactoring: Individual -> Record, plus additional EA variant
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,147 @@ | ||
| package aitoa.algorithms; | ||
|
|
||
| import java.io.IOException; | ||
| import java.io.Writer; | ||
| import java.util.Random; | ||
|
|
||
| import aitoa.structure.IBinarySearchOperator; | ||
| import aitoa.structure.IBlackBoxProcess; | ||
| import aitoa.structure.INullarySearchOperator; | ||
| import aitoa.structure.ISpace; | ||
| import aitoa.structure.IUnarySearchOperator; | ||
| import aitoa.structure.LogFormat; | ||
| import aitoa.structure.Metaheuristic2; | ||
| import aitoa.structure.Record; | ||
| import aitoa.utils.Experiment; | ||
|
|
||
| /** | ||
| * A variant of the EA where each offspring competes with their | ||
| * directly corresponding parent solution only. It is something | ||
| * like a set of parallel {@link EA1p1}, but the addition of | ||
| * {@linkplain aitoa.structure.IBinarySearchOperator crossover}. | ||
| * | ||
| * @param <X> | ||
| * the search space | ||
| * @param <Y> | ||
| * the solution space | ||
| */ | ||
| // start relevant | ||
| public final class EA2<X, Y> extends Metaheuristic2<X, Y> { | ||
| // end relevant | ||
|
|
||
| /** the crossover rate */ | ||
| public final double cr; | ||
| /** the number of selected parents */ | ||
| public final int mu; | ||
|
|
||
| /** | ||
| * Create a new instance of the evolutionary algorithm | ||
| * | ||
| * @param pNullary | ||
| * the nullary search operator. | ||
| * @param pUnary | ||
| * the unary search operator | ||
| * @param pBinary | ||
| * the binary search operator | ||
| * @param pCr | ||
| * the crossover rate | ||
| * @param pMu | ||
| * the number of parents to be selected | ||
| */ | ||
| public EA2(final INullarySearchOperator<X> pNullary, | ||
| final IUnarySearchOperator<X> pUnary, | ||
| final IBinarySearchOperator<X> pBinary, final double pCr, | ||
| final int pMu) { | ||
| super(pNullary, pUnary, pBinary); | ||
| if ((pCr < 0d) || (pCr > 1d) || (!(Double.isFinite(pCr)))) { | ||
| throw new IllegalArgumentException( | ||
| "Invalid crossover rate: " + pCr); //$NON-NLS-1$ | ||
| } | ||
| this.cr = pCr; | ||
| if ((pMu < 1) || (pMu > 1_000_000)) { | ||
| throw new IllegalArgumentException("Invalid mu: " + pMu); //$NON-NLS-1$ | ||
| } | ||
| if ((pMu <= 1) && (pCr > 0d)) { | ||
| throw new IllegalArgumentException(// | ||
| "crossover rate must be 0 if mu is 1, but cr is " //$NON-NLS-1$ | ||
| + pCr); | ||
| } | ||
| this.mu = pMu; | ||
| } | ||
|
|
||
| /** {@inheritDoc} */ | ||
| @SuppressWarnings("unchecked") | ||
| @Override | ||
| // start relevant | ||
| public void solve(final IBlackBoxProcess<X, Y> process) { | ||
| // omitted: initialize local variables random, searchSpace, and | ||
| // array P of length mu and variable dest for new solution | ||
| // end relevant | ||
| // create local variables | ||
| final Random random = process.getRandom(); | ||
| final ISpace<X> searchSpace = process.getSearchSpace(); | ||
| int p2; // to hold index of second selected record | ||
|
|
||
| final Record<X>[] P = new Record[this.mu]; | ||
| Record<X> dest = | ||
| new Record<>(searchSpace.create(), Double.NaN); | ||
| // start relevant | ||
| // first generation: fill population with random solutions | ||
| for (int i = P.length; (--i) >= 0;) { | ||
| final X x = searchSpace.create(); // allocate point | ||
| this.nullary.apply(x, random); // fill with random data | ||
| P[i] = new Record<>(x, process.evaluate(x)); // evaluate | ||
| // end relevant | ||
| if (process.shouldTerminate()) { // we return | ||
| return; // best solution is stored in process | ||
| } | ||
| // start relevant | ||
| } | ||
|
|
||
| int p1 = -1; // index to iterate over first parent | ||
| while (!process.shouldTerminate()) { // main loop | ||
| p1 = (p1 + 1) % this.mu; // loop over parent population | ||
| final Record<X> s1 = P[p1]; | ||
| if (random.nextDouble() <= this.cr) { // crossover! | ||
| do { // find a second, different record | ||
| p2 = random.nextInt(this.mu); | ||
| } while (p2 == p1); // repeat until p1 != p2 | ||
| // perform recombination of the two selected solutions | ||
| this.binary.apply(s1.x, P[p2].x, dest.x, random); | ||
| } else { // perform unary operation (i.e., mutation) | ||
| // create modified copy of parent using unary operator | ||
| this.unary.apply(s1.x, dest.x, random); | ||
| } // end mutation | ||
| dest.quality = process.evaluate(dest.x); | ||
| if (dest.quality <= s1.quality) { // compare dest with s1 | ||
| P[p1] = dest; | ||
| dest = s1; | ||
| } | ||
| } // the end of the main loop | ||
| } | ||
| // end relevant | ||
|
|
||
| /** {@inheritDoc} */ | ||
| @Override | ||
| public void printSetup(final Writer output) | ||
| throws IOException { | ||
| output.write(LogFormat.mapEntry(// | ||
| LogFormat.SETUP_BASE_ALGORITHM, "ea2")); //$NON-NLS-1$ | ||
| output.write(System.lineSeparator()); | ||
| super.printSetup(output); | ||
| output.write(LogFormat.mapEntry("mu", this.mu));///$NON-NLS-1$ | ||
| output.write(System.lineSeparator()); | ||
| output.write(LogFormat.mapEntry("cr", this.cr));//$NON-NLS-1$ | ||
| output.write(System.lineSeparator()); | ||
| } | ||
|
|
||
| /** {@inheritDoc} */ | ||
| @Override | ||
| public String toString() { | ||
| return Experiment.nameFromObjectsMerge(((("ea2_" + //$NON-NLS-1$ | ||
| this.mu) + '@') + this.cr), // | ||
| this.unary, this.binary); | ||
| } | ||
| // start relevant | ||
| } | ||
| // end relevant |
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