57 nlp.
subjectTo( 0.0 <= y2 - 5.0*
exp(-y1) - 2.0*
exp(-0.5*(y1-3.0)*(y1-3.0)) );
85 algorithm.
getWeights(
"scalar2_nnc_weights.txt");
100 window2.
addSubplot( paretoFront,
"Pareto Front (with filter) y1 vs y2",
"y1",
"y2",
PM_POINTS );
returnValue print(std::ostream &stream=std::cout, const char *const name=DEFAULT_LABEL, const char *const startString=DEFAULT_START_STRING, const char *const endString=DEFAULT_END_STRING, uint width=DEFAULT_WIDTH, uint precision=DEFAULT_PRECISION, const char *const colSeparator=DEFAULT_COL_SEPARATOR, const char *const rowSeparator=DEFAULT_ROW_SEPARATOR) const
virtual returnValue solve()
DMatrix getWeights() const
virtual returnValue plot(PlotFrequency _frequency=PLOT_IN_ANY_CASE)
#define USING_NAMESPACE_ACADO
Provides a time grid consisting of vector-valued optimization variables at each grid point...
returnValue initializeParameters(const char *fileName)
returnValue subjectTo(const DifferentialEquation &differentialEquation_)
returnValue getParetoFrontWithFilter(VariablesGrid &paretoFront) const
returnValue addSubplot(PlotWindowSubplot &_subplot)
returnValue minimize(const Expression &arg)
returnValue set(OptionsName name, int value)
returnValue getWeightsWithFilter(const char *fileName) const
Data class for defining static optimization problems.
returnValue getParetoFront(VariablesGrid &paretoFront) const
virtual returnValue solveSingleObjective(const int &number)
IntermediateState exp(const Expression &arg)
User-interface to formulate and solve optimal control problems with multiple objectives.
Provides an interface to Gnuplot for plotting algorithmic outputs.