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/* |
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* Written by Doug Lea and Bill Scherer with assistance from members |
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* of JCP JSR-166 Expert Group and released to the public domain, as |
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* explained at http://creativecommons.org/licenses/publicdomain |
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* explained at http://creativecommons.org/publicdomain/zero/1.0/ |
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*/ |
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import java.util.*; |
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// Thread.sleep(100); |
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long elapsed = stopTime - startTime; |
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double secs = (double)elapsed / 1000000000.0; |
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double secs = (double) elapsed / 1000000000.0; |
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p.printSnapshot(secs); |
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} |
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*/ |
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void printSnapshot(double secs) { |
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int xs = totalExchanges(); |
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long rate = (xs == 0)? 0L : (long)((secs * 1000000000.0) / xs); |
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long rate = (xs == 0) ? 0L : (long) ((secs * 1000000000.0) / xs); |
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Chromosome bestc = subpops[0].chromosomes[0]; |
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Chromosome worstc = bestc; |
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for (int k = 0; k < subpops.length; ++k) { |
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} |
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public int compareTo(Object x) { // to enable sorting |
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int xf = ((Chromosome)x).fitness; |
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int xf = ((Chromosome) x).fitness; |
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int f = fitness; |
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return ((f == xf)? 0 :((f < xf)? -1 : 1)); |
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return ((f == xf) ? 0 :((f < xf) ? -1 : 1)); |
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} |
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void recalcFitness() { |
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f += cities.distanceBetween(p, n); |
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p = n; |
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} |
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fitness = (int)(f / len); |
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fitness = (int) (f / len); |
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} |
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/** |
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for (int i = 0; i < n; i++) { |
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for (int j = 0; j < n; j++) { |
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double dx = (double)xPts[i] - (double)xPts[j]; |
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double dy = (double)yPts[i] - (double)yPts[j]; |
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double dx = (double) xPts[i] - (double) xPts[j]; |
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double dy = (double) yPts[i] - (double) yPts[j]; |
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double dd = Math.hypot(dx, dy) / 2.0; |
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long ld = Math.round(dd); |
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distances[i][j] = (ld >= Integer.MAX_VALUE)? |
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Integer.MAX_VALUE : (int)ld; |
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distances[i][j] = (ld >= Integer.MAX_VALUE) ? |
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Integer.MAX_VALUE : (int) ld; |
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} |
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} |
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} |
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/** |
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* Returns the cached distance between a pair of cities |
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* Returns the cached distance between a pair of cities. |
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*/ |
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int distanceBetween(int i, int j) { |
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return distances[i][j]; |
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} |
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// Scale ints to doubles in [0,1) |
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static final double PSCALE = (double)0x80000000L; |
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static final double PSCALE = (double) 0x80000000L; |
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/** |
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* Return distance for points scaled in [0,1). This simplifies |
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* Returns distance for points scaled in [0,1). This simplifies |
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* checking results. The expected optimal TSP for random |
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* points is believed to be around 0.76 * sqrt(N). For papers |
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* discussing this, see |
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* http://www.densis.fee.unicamp.br/~moscato/TSPBIB_home.html |
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*/ |
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double unitDistanceBetween(int i, int j) { |
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double dx = ((double)xPts[i] - (double)xPts[j]) / PSCALE; |
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double dy = ((double)yPts[i] - (double)yPts[j]) / PSCALE; |
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double dx = ((double) xPts[i] - (double) xPts[j]) / PSCALE; |
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double dy = ((double) yPts[i] - (double) yPts[j]) / PSCALE; |
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return Math.hypot(dx, dy); |
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} |
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