ZDT4.h
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1//===========================================================================
2/*!
3 *
4 *
5 * \brief Multi-objective optimization benchmark function ZDT4
6 *
7 * The function is described in
8 *
9 * Eckart Zitzler, Kalyanmoy Deb, and Lothar Thiele. Comparison of
10 * Multiobjective Evolutionary Algorithms: Empirical
11 * Results. Evolutionary Computation 8(2):173-195, 2000
12 *
13 *
14 *
15 * \author -
16 * \date -
17 *
18 *
19 * \par Copyright 1995-2017 Shark Development Team
20 *
21 * <BR><HR>
22 * This file is part of Shark.
23 * <https://shark-ml.github.io/Shark/>
24 *
25 * Shark is free software: you can redistribute it and/or modify
26 * it under the terms of the GNU Lesser General Public License as published
27 * by the Free Software Foundation, either version 3 of the License, or
28 * (at your option) any later version.
29 *
30 * Shark is distributed in the hope that it will be useful,
31 * but WITHOUT ANY WARRANTY; without even the implied warranty of
32 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
33 * GNU Lesser General Public License for more details.
34 *
35 * You should have received a copy of the GNU Lesser General Public License
36 * along with Shark. If not, see <http://www.gnu.org/licenses/>.
37 *
38 */
39//===========================================================================
40
41#ifndef SHARK_OBJECTIVEFUNCTIONS_BENCHMARK_ZDT4_H
42#define SHARK_OBJECTIVEFUNCTIONS_BENCHMARK_ZDT4_H
43
44#include <shark/ObjectiveFunctions/AbstractObjectiveFunction.h>
45#include <shark/ObjectiveFunctions/BoxConstraintHandler.h>
46
47namespace shark {namespace benchmarks{
48/*! \brief Multi-objective optimization benchmark function ZDT4
49*
50* The function is described in
51* This function is highly multimodal
52*
53* Eckart Zitzler, Kalyanmoy Deb, and Lothar Thiele. Comparison of
54* Multiobjective Evolutionary Algorithms: Empirical
55* Results. Evolutionary Computation 8(2):173-195, 2000
56* \ingroup benchmarks
57*/
58struct ZDT4 : public MultiObjectiveFunction
59{
60
61 ZDT4(std::size_t numVariables = 1) {
62 announceConstraintHandler(&m_handler);
63 setNumberOfVariables(numVariables);
64 }
65
66 /// \brief From INameable: return the class name.
67 std::string name() const
68 { return "ZDT4"; }
69
70 std::size_t numberOfObjectives()const{
71 return 2;
72 }
73
74 std::size_t numberOfVariables()const{
75 return m_handler.dimensions();
76 }
77
78 bool hasScalableDimensionality()const{
79 return true;
80 }
81
82 /// \brief Adjusts the number of variables if the function is scalable.
83 /// \param [in] numberOfVariables The new dimension.
84 void setNumberOfVariables( std::size_t numberOfVariables ){
85 RealVector lower(numberOfVariables,-5);
86 RealVector upper(numberOfVariables,5);
87 lower(0) = 0;
88 upper(0) = 1;
89 m_handler.setBounds(lower,upper);
90 }
91
92 ResultType eval( const SearchPointType & x ) const {
93 m_evaluationCounter++;
94
95 ResultType value( 2 );
96
97 value[0] = x( 0 );
98
99 double sum = 0.0;
100 for (unsigned i = 1; i < numberOfVariables(); i++)
101 sum +=sqr(x( i )) - (10.0 * cos(4 * M_PI * x(i) ) );
102
103 double g = 1.0 + (10.0 * (numberOfVariables() - 1.0)) + sum;
104 double h = 1.0 - std::sqrt(x(0) / g);
105
106 value[1] = g * h;
107
108 return value;
109 }
110
111private:
112 BoxConstraintHandler<SearchPointType> m_handler;
113};
114
115}}
116#endif