Optimization BobyqaThis block finds the least value of a function of many variables by applying a trust region method that forms quadratic models by interpolation. Some freedom is usually present in the interpolation conditions, which are taken up by minimizing the Frobenius norm of the change to the second derivative of the model, beginning with the zero matrix. The values of the variables are constrained by upper and lower bounds.BobyqaOptThis block finds the least value of a function of many variables by applying a trust region method that forms quadratic models by interpolation. Some freedom is usually present in the interpolation conditions that are taken up by minimizing the Frobenius norm of the change to the second derivative of the model, beginning with the zero matrix. The values of the variables are constrained by upper and lower bounds.
Optimization BobyqaThis block finds the least value of a function of many variables by applying a trust region method that forms quadratic models by interpolation. Some freedom is usually present in the interpolation conditions, which are taken up by minimizing the Frobenius norm of the change to the second derivative of the model, beginning with the zero matrix. The values of the variables are constrained by upper and lower bounds.BobyqaOptThis block finds the least value of a function of many variables by applying a trust region method that forms quadratic models by interpolation. Some freedom is usually present in the interpolation conditions that are taken up by minimizing the Frobenius norm of the change to the second derivative of the model, beginning with the zero matrix. The values of the variables are constrained by upper and lower bounds.
