[shark] 21/58: Fast hypervolume algorithm for three objectives added.
Ghislain Vaillant
ghisvail-guest at moszumanska.debian.org
Wed Mar 16 10:05:29 UTC 2016
This is an automated email from the git hooks/post-receive script.
ghisvail-guest pushed a commit to branch master
in repository shark.
commit 1e32bddc2998ead1c252428056b6c2f14ff8582f
Author: Tobias Glasmachers <tobias.glasmachers at ini.rub.de>
Date: Mon Feb 8 09:41:12 2016 +0100
Fast hypervolume algorithm for three objectives added.
---
Test/Algorithms/Hypervolume.cpp | 13 +--
.../DirectSearch/HypervolumeCalculator.h | 121 +++++++++++++++++++--
2 files changed, 113 insertions(+), 21 deletions(-)
diff --git a/Test/Algorithms/Hypervolume.cpp b/Test/Algorithms/Hypervolume.cpp
index 1b7687f..81852d0 100644
--- a/Test/Algorithms/Hypervolume.cpp
+++ b/Test/Algorithms/Hypervolume.cpp
@@ -22,9 +22,6 @@ struct Fixture {
Fixture() {
BOOST_TEST_MESSAGE( "Setting up test sets and reference points " );
m_refPoint3D = boost::assign::list_of( 1.1 )( 1.1 )( 1.1 );
- //~ m_refPoint3D.push_back(1.1);
- //~ m_refPoint3D.push_back(1.1);
- //~ m_refPoint3D.push_back(1.1);
m_testSet3D.push_back( boost::assign::list_of( 6.56039859404455e-2 ) (0.4474014917277) (0.891923776019316) );
m_testSet3D.push_back( boost::assign::list_of( 3.74945443950542e-2)(3.1364039802686e-2)(0.998804513479922 ) );
m_testSet3D.push_back( boost::assign::list_of( 0.271275894554688)(0.962356894778677)(1.66911984440026e-2 ) );
@@ -106,9 +103,8 @@ BOOST_AUTO_TEST_CASE( Algorithms_ExactHypervolume ) {
BOOST_CHECK_CLOSE( hc( ife, m_testSet2D, m_refPoint2D ), Fixture::HV_TEST_SET_2D, 1E-5 );
BOOST_CHECK_CLOSE( hc( ife, m_testSet3D, m_refPoint3D ), Fixture::HV_TEST_SET_3D, 1E-5 );
-
std::vector<double> results;
-
+
for( unsigned int trial = 0; trial < 10; trial++ )
results.push_back(ha( m_testSet3D.begin(), m_testSet3D.end(), ife, m_refPoint3D, 1E-2, 1E-2 ) );
@@ -130,10 +126,9 @@ BOOST_AUTO_TEST_CASE( Algorithms_LeastContributorApproximator ) {
}
std::vector< RealVector >::const_iterator it = m_testSet3D.begin();
- BOOST_CHECK_EQUAL(
- lca.leastContributor( ife, m_testSet3D, m_refPoint3D ),
- (std::size_t)std::distance( contributions.begin(), std::min_element( contributions.begin(), contributions.end() ) )
- );
+ std::size_t approx = lca.leastContributor( ife, m_testSet3D, m_refPoint3D );
+ std::size_t exact = (std::size_t)std::distance( contributions.begin(), std::min_element( contributions.begin(), contributions.end() ) );
+ BOOST_CHECK_EQUAL( approx, exact );
}
BOOST_AUTO_TEST_SUITE_END()
diff --git a/include/shark/Algorithms/DirectSearch/HypervolumeCalculator.h b/include/shark/Algorithms/DirectSearch/HypervolumeCalculator.h
index 0992a3a..aa42954 100644
--- a/include/shark/Algorithms/DirectSearch/HypervolumeCalculator.h
+++ b/include/shark/Algorithms/DirectSearch/HypervolumeCalculator.h
@@ -5,18 +5,24 @@
*
* The algorithm is described in
*
- * Nicola Beume und G�nter Rudolph.
+ * Nicola Beume und Günter Rudolph.
* Faster S-Metric Calculation by Considering Dominated Hypervolume as Klee's Measure Problem.
* In: B. Kovalerchuk (ed.): Proceedings of the Second IASTED Conference on Computational Intelligence (CI 2006),
* pp. 231-236. ACTA Press: Anaheim, 2006.
*
- *
+ * A specialized algorithm is used for the three-objective case:
+ *
+ * M. T. M. Emmerich and C. M. Fonseca.
+ * Computing hypervolume contributions in low dimensions: Asymptotically optimal algorithm and complexity results.
+ * In: Evolutionary Multi-Criterion Optimization (EMO) 2011.
+ * Vol. 6576 of Lecture Notes in Computer Science, pp. 121--135, Berlin: Springer, 2011.
*
- * \author T.Voss, O.Krause
- * \date 2014
*
+ * \author T.Voss, O.Krause, T. Glasmachers
+ * \date 2014-2016
*
- * \par Copyright 1995-2015 Shark Development Team
+ *
+ * \par Copyright 1995-2016 Shark Development Team
*
* <BR><HR>
* This file is part of Shark.
@@ -44,7 +50,7 @@
#include <algorithm>
#include <iostream>
#include <vector>
-
+#include <map>
#include <cmath>
namespace shark {
@@ -53,7 +59,7 @@ namespace shark {
*
* The algorithm is described in
*
- * Nicola Beume und G�nter Rudolph.
+ * Nicola Beume und Günter Rudolph.
* Faster S-Metric Calculation by Considering Dominated Hypervolume as Klee's Measure Problem.
* In: B. Kovalerchuk (ed.): Proceedings of the Second IASTED Conference on Computational Intelligence (CI 2006),
* pp. 231-236. ACTA Press: Anaheim, 2006.
@@ -63,7 +69,7 @@ namespace shark {
/**
* \brief Returns an estimate on the runtime of the algorithm.
* \param [in] noPoints The number of points n considered in the runtime estimation.
- * \param [in] noObjectives The number of points m considered in the runtime estimation.
+ * \param [in] noObjectives The number of objectives m considered in the runtime estimation.
*/
static double runtime( std::size_t noPoints, std::size_t noObjectives ) {
if( noPoints < 10 )
@@ -190,12 +196,103 @@ namespace shark {
}
return h;
}
+ else if (m_noObjectives == 3)
+ {
+ if (m_useLogHyp)
+ {
+ double volume = 0.0;
+ double area = 0.0;
+ std::map<double, double> front2D;
+ double prev_x2 = 0.0;
+ for (size_t i=0; i<set.size(); i++)
+ {
+ VectorType x = extractor(set[i]);
+ if (i > 0) volume += area * (std::log(x[2]) - prev_x2);
+
+ // check whether x is dominated
+ std::map<double, double>::iterator worse = front2D.upper_bound(std::log(x[0]));
+ double b = std::log(refPoint[1]);
+ if (worse != front2D.begin())
+ {
+ std::map<double, double>::iterator better = worse;
+ if (better == front2D.end() || better->first > std::log(x[0])) --better;
+ if (better->second <= std::log(x[1])) continue;
+ b = better->second;
+ }
+
+ // remove dominated points
+ while (worse != front2D.end())
+ {
+ if (worse->second < std::log(x[1])) break;
+ std::map<double, double>::iterator it = worse;
+ ++worse;
+ double r = (worse == front2D.end()) ? std::log(refPoint[0]): worse->first;
+ area -= (r - it->first) * (b - it->second);
+ front2D.erase(it);
+ }
+
+ // insert x
+ front2D[std::log(x[0])] = std::log(x[1]);
+ double r = (worse == front2D.end()) ? std::log(refPoint[0]) : worse->first;
+ area += (r - std::log(x[0])) * (b - std::log(x[1]));
+
+ prev_x2 = std::log(x[2]);
+ }
+ volume += area * (std::log(refPoint[2]) - prev_x2);
+ return volume;
+ }
+ else
+ {
+ double volume = 0.0;
+ double area = 0.0;
+ std::map<double, double> front2D;
+ double prev_x2 = 0.0;
+ for (size_t i=0; i<set.size(); i++)
+ {
+ VectorType x = extractor(set[i]);
+ if (i > 0) volume += area * (x[2] - prev_x2);
+
+ // check whether x is dominated
+ std::map<double, double>::iterator worse = front2D.upper_bound(x[0]);
+ double b = refPoint[1];
+ if (worse != front2D.begin())
+ {
+ std::map<double, double>::iterator better = worse;
+ if (better == front2D.end() || better->first > x[0]) --better;
+ if (better->second <= x[1]) continue;
+ b = better->second;
+ }
+
+ // remove dominated points
+ while (worse != front2D.end())
+ {
+ if (worse->second < x[1]) break;
+ std::map<double, double>::iterator it = worse;
+ ++worse;
+ double r = (worse == front2D.end()) ? refPoint[0]: worse->first;
+ area -= (r - it->first) * (b - it->second);
+ front2D.erase(it);
+ }
- VectorType regLow( m_noObjectives, 1E15 );
- for( std::size_t i = 0; i < set.size(); i++ ){
- noalias(regLow) = min(regLow,extractor(set[i]));
+ // insert x
+ front2D[x[0]] = x[1];
+ double r = (worse == front2D.end()) ? refPoint[0] : worse->first;
+ area += (r - x[0]) * (b - x[1]);
+
+ prev_x2 = x[2];
+ }
+ volume += area * (refPoint[2] - prev_x2);
+ return volume;
+ }
+ }
+ else
+ {
+ VectorType regLow( m_noObjectives, 1E15 );
+ for( std::size_t i = 0; i < set.size(); i++ ){
+ noalias(regLow) = min(regLow,extractor(set[i]));
+ }
+ return( stream( regLow, refPoint, set, extractor, 0, refPoint.back() ) );
}
- return( stream( regLow, refPoint, set, extractor, 0, refPoint.back() ) );
}
template<typename VectorType>
--
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