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OPTK
0.1.2
Toolkit for global optimisation algorithms
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#include <synthetic.hpp>
Public Member Functions | |
| double | evaluate (inst::set x) override |
Public Member Functions inherited from syn::synthetic | |
| synthetic (const std::string &n, u_int dims, double lb, double ub, double opt) | |
| synthetic (const std::string &n, u_int dims, double opt) | |
| ~synthetic () | |
| sspace::sspace_t * | get_search_space () |
| void | set_properties (std::vector< properties > p) |
| std::vector< properties > | get_properties () |
| inst::set | get_opt_param () |
| double | get_opt () |
| void | update_opt (double opt) |
| u_int | get_dims () |
| void | validate_param_set (inst::set x) |
Public Member Functions inherited from optk::benchmark | |
| benchmark (const std::string &name) | |
| std::string | get_name () |
Additional Inherited Members | |
Protected Member Functions inherited from syn::synthetic | |
| void | set_opt_param (inst::set op) |
Protected Attributes inherited from syn::synthetic | |
| u_int | m_dims |
| double | m_lb |
| double | m_ub |
| double | m_opt |
| std::vector< properties > | m_properties |
| inst::set | opt_params |
| sspace::sspace_t | m_sspace |
Protected Attributes inherited from optk::benchmark | |
| std::string | m_name |
Judge's function has the following formula:
\[ f(\mathbf{x}) = \sum^{20}_{i=1}\left( (x_1 + B_ix_2 + C_ix_2^2) - A_i \right)^2 \]
, where the vectors A, B and C are given by:
\[ \begin{align*} A &= \begin{bmatrix} 4.284 & 4.149 & 3.877 & 0.533 & 2.211 & 2.389 & 2.145 & 3.231 & 1.998 & 1.379 & 2.106 & 1.428 & 1.011 & 2.179 & 2.858 & 1.388 & 1.651 & 1.593 & 1.046 & 2.152 \end{bmatrix} \\ B &= \begin{bmatrix} 0.286 & 0.973 & 0.384 & 0.276 & 0.973 & 0.543 & 0.957 & 0.948 & 0.543 & 0.797 & 0.936 & 0.889 & 0.006 & 0.828 & 0.399 & 0.617 & 0.939 & 0.784 & 0.072 & 0.889 \end{bmatrix} \\ C &= \begin{bmatrix} 0.645 & 0.585 & 0.310 & 0.058 & 0.455 & 0.779 & 0.259 & 0.202 & 0.028 & 0.099 & 0.142 & 0.296 & 0.175 & 0.180 & 0.842 & 0.039 & 0.103 & 0.620 & 0.158 & 0.704 \end{bmatrix} \end{align*} \]
subject to \(-10 \le x_i \le 10\) for \(i = 1,2\$, with a global minimum located at \){x}^* = (0.86479, 1.2357) \( with value \)({x}^*) = 16.0817307 \(. */ class judge: public synthetic { public: judge (); double evaluate (inst::set x) override; }; /** The Langermann 2 function has the following formula: \f[ f(\mathbf{x}) = -\sum^m_{i=1}c_i e^{-\frac{1}{\pi} \sum^D_{j=1}(x_j-a_{ij})^2} \cos\left(\pi\sum^D_{j=1}(x_j-a_{ij})^2\right), \f] where \){a} \(, \){b} \( and \){c} \( are the following vectors: \f[ \begin{align*} \mathbf{a} &= \begin{bmatrix} 3 & 5 & 2 & 1 & 7 \end{bmatrix} \\ \mathbf{b} &= \begin{bmatrix} 5 & 2 & 1 & 4 & 9 \end{bmatrix} \\ \mathbf{c} &= \begin{bmatrix} 1 & 2 & 5 & 2 & 3 \end{bmatrix}. \f] The parameters are subject to \) x_i 10 \( and there is a global minimum located at \){x}^* = (2.00299219, 1.006096) \( with value \)({x}^*) = -5.1621259
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overridevirtual |
Evaluate the benchmark (i.e. calculate the value of the objective fuinction) on the provided values.
| x | A vector of double-precision values to evaluate the benchmark at. |
Implements optk::benchmark.
1.8.13