algo= class=TNC class=OptimizationAlgorithmImplementation problem=class=OptimizationProblem implementation=class=OptimizationProblemImplementation objective=class=Function name=Unnamed implementation=class=FunctionImplementation name=Unnamed description=[x1,x2,x3,x4,y1] evaluationImplementation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x1,x2,x3,x4] outputVariablesNames=[y1] formulas=[x1+2*x2-3*x3+4*x4] gradientImplementation=class=SymbolicGradient name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x1,x2,x3,x4] outputVariablesNames=[y1] formulas=[x1+2*x2-3*x3+4*x4] hessianImplementation=class=SymbolicHessian name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x1,x2,x3,x4] outputVariablesNames=[y1] formulas=[x1+2*x2-3*x3+4*x4] equality constraint=none inequality constraint=none bounds=class=Interval name=Unnamed dimension=4 lower bound=class=Point name=Unnamed dimension=4 values=[-3,-3,-3,-3] upper bound=class=Point name=Unnamed dimension=4 values=[5,5,5,5] finite lower bound=[1,1,1,1] finite upper bound=[1,1,1,1] minimization=true dimension=4 startingPoint=class=Point name=Unnamed dimension=4 values=[0,0,0,0] maximumIterationNumber=100 maximumEvaluationNumber=100000 maximumAbsoluteError=1e-05 maximumRelativeError=1e-05 maximumResidualError=1e-05 maximumConstraintError=1e-05 verbose=false scale=class=Point name=Unnamed dimension=0 values=[] offset=class=Point name=Unnamed dimension=0 values=[] maxCGit=50 eta=0.25 stepmx=10 accuracy=0.0001 fmin=1 rescale=1.3
result= [-3.0000,-3.0000,5.0000,-3.0000]
multipliers= [-1.0000,-2.0000,0.0000,-4.0000,0.0000,0.0000,-3.0000,0.0000]
algo= class=TNC class=OptimizationAlgorithmImplementation problem=class=OptimizationProblem implementation=class=OptimizationProblemImplementation objective=class=Function name=Unnamed implementation=class=FunctionImplementation name=Unnamed description=[x1,x2,x3,x4,y1] evaluationImplementation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x1,x2,x3,x4] outputVariablesNames=[y1] formulas=[x1+2*x2-3*x3+4*x4] gradientImplementation=class=SymbolicGradient name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x1,x2,x3,x4] outputVariablesNames=[y1] formulas=[x1+2*x2-3*x3+4*x4] hessianImplementation=class=SymbolicHessian name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x1,x2,x3,x4] outputVariablesNames=[y1] formulas=[x1+2*x2-3*x3+4*x4] equality constraint=none inequality constraint=none bounds=class=Interval name=Unnamed dimension=4 lower bound=class=Point name=Unnamed dimension=4 values=[-3,-3,-3,-3] upper bound=class=Point name=Unnamed dimension=4 values=[5,5,5,5] finite lower bound=[1,1,1,1] finite upper bound=[1,1,1,1] minimization=false dimension=4 startingPoint=class=Point name=Unnamed dimension=4 values=[0,0,0,0] maximumIterationNumber=100 maximumEvaluationNumber=100000 maximumAbsoluteError=1e-05 maximumRelativeError=1e-05 maximumResidualError=1e-05 maximumConstraintError=1e-05 verbose=false scale=class=Point name=Unnamed dimension=0 values=[] offset=class=Point name=Unnamed dimension=0 values=[] maxCGit=50 eta=0.25 stepmx=10 accuracy=0.0001 fmin=1 rescale=1.3
result= [5.0000,5.0000,-3.0000,5.0000]
multipliers= [0.0000,0.0000,3.0000,0.0000,1.0000,2.0000,0.0000,4.0000]
algo= class=TNC class=OptimizationAlgorithmImplementation problem=class=OptimizationProblem implementation=class=OptimizationProblemImplementation objective=class=Function name=Unnamed implementation=class=FunctionImplementation name=Unnamed description=[x1,x2,x3,x4,y1] evaluationImplementation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x1,x2,x3,x4] outputVariablesNames=[y1] formulas=[x1*cos(x1)+2*x2*x3-3*x3+4*x3*x4] gradientImplementation=class=SymbolicGradient name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x1,x2,x3,x4] outputVariablesNames=[y1] formulas=[x1*cos(x1)+2*x2*x3-3*x3+4*x3*x4] hessianImplementation=class=SymbolicHessian name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x1,x2,x3,x4] outputVariablesNames=[y1] formulas=[x1*cos(x1)+2*x2*x3-3*x3+4*x3*x4] equality constraint=none inequality constraint=none bounds=class=Interval name=Unnamed dimension=4 lower bound=class=Point name=Unnamed dimension=4 values=[-3,-3,-3,-3] upper bound=class=Point name=Unnamed dimension=4 values=[5,5,5,5] finite lower bound=[1,1,1,1] finite upper bound=[1,1,1,1] minimization=true dimension=4 startingPoint=class=Point name=Unnamed dimension=4 values=[3,-2.5,4.5,-2.5] maximumIterationNumber=100 maximumEvaluationNumber=100000 maximumAbsoluteError=1e-05 maximumRelativeError=1e-05 maximumResidualError=1e-05 maximumConstraintError=1e-05 verbose=false scale=class=Point name=Unnamed dimension=0 values=[] offset=class=Point name=Unnamed dimension=0 values=[] maxCGit=50 eta=0.25 stepmx=10 accuracy=0.0001 fmin=1 rescale=1.3
result= [3.4256,-3.0000,5.0000,-3.0000]
multipliers= [0.0000,-10.0000,0.0000,-20.0000,0.0000,0.0000,-21.0000,0.0000]
algo= class=TNC class=OptimizationAlgorithmImplementation problem=class=OptimizationProblem implementation=class=OptimizationProblemImplementation objective=class=Function name=Unnamed implementation=class=FunctionImplementation name=Unnamed description=[x1,x2,x3,x4,y1] evaluationImplementation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x1,x2,x3,x4] outputVariablesNames=[y1] formulas=[x1*cos(x1)+2*x2*x3-3*x3+4*x3*x4] gradientImplementation=class=SymbolicGradient name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x1,x2,x3,x4] outputVariablesNames=[y1] formulas=[x1*cos(x1)+2*x2*x3-3*x3+4*x3*x4] hessianImplementation=class=SymbolicHessian name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x1,x2,x3,x4] outputVariablesNames=[y1] formulas=[x1*cos(x1)+2*x2*x3-3*x3+4*x3*x4] equality constraint=none inequality constraint=none bounds=class=Interval name=Unnamed dimension=4 lower bound=class=Point name=Unnamed dimension=4 values=[-3,-3,-3,-3] upper bound=class=Point name=Unnamed dimension=4 values=[5,5,5,5] finite lower bound=[1,1,1,1] finite upper bound=[1,1,1,1] minimization=false dimension=4 startingPoint=class=Point name=Unnamed dimension=4 values=[3,-2.5,4.5,-2.5] maximumIterationNumber=100 maximumEvaluationNumber=100000 maximumAbsoluteError=1e-05 maximumRelativeError=1e-05 maximumResidualError=1e-05 maximumConstraintError=1e-05 verbose=false scale=class=Point name=Unnamed dimension=0 values=[] offset=class=Point name=Unnamed dimension=0 values=[] maxCGit=50 eta=0.25 stepmx=10 accuracy=0.0001 fmin=1 rescale=1.3
result= [-3.0000,5.0000,5.0000,5.0000]
multipliers= [1.4134,0.0000,0.0000,0.0000,0.0000,10.0000,27.0000,20.0000]
