What Is Optimization Toolbox?
What Is Optimization Toolbox? What Is Optimization Toolbox?
5 Optimization ToolFunction Value CheckWhen selected, Function value check examines the values returned bythe user-supplied objective function, or nonlinear constraint function, andproduces an error if the user-supplied function returns Inf, NaN, orcomplexvalues.Note Function value check does not produce an error for Inf when usedwith fminbnd, fminsearch, orfzero, which handle Inf appropriately.User-Supplied DerivativesSelecting Validate user-supplied derivatives performs an evaluationof the derivatives in the objective and nonlinear constraint functions. Atruntime, a warning message is displayed if the computed and providedderivatives disagree.Jacobian sparsity pattern specifies the sparsity pattern (locations of thenonzeros) of the Jacobian for finite differencing. Given that you provide thissparsity pattern, the solver approximates the Jacobian using sparse finitedifferences. If the structure is unknown, you can set this option to a densematrix (the default value), but note that this can be expensive for largeproblems, so it is best to determine the sparsity structure.Jacobian multiply function specifies the function handle for a multiplyfunction. This function computes Jacobian-matrix products without formingthe Jacobian. Note that this option is only available when the Derivativesfield is set to Jacobian supplied in objective function.Hessian sparsity pattern specifies the sparsity pattern (locations of thenonzeros) of the Hessian for finite differencing. Given that you provide thissparsity pattern, the solver approximates the Hessian using sparse finitedifferences of the gradient. If the structure is unknown, you can set this5-32
Specifying the Optionsoption to a dense matrix (the default value). Note that this can be expensivefor large problems, so it is best to determine the sparsity structure.Hessian multiply function specifies the function handle for a multiplyfunction. This function computes Hessian-matrix products without formingthe Hessian, but note that this option is only available when the Derivativesfield is set to Gradient and Hessian supplied in objective function.The graphic above shows the user-supplied derivative options available forthe fmincon default solver.Approximated DerivativesWhen finite differences are used to approximate the derivatives, you canadjust the following options:• Minimum perturbation for specifying the minimum change in variablesfor finite differencing derivative approximations.• Maximum perturbation for specifying the maximum change in variablesfor finite differencing derivative approximations.5-33
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5 <strong>Optimization</strong> ToolFunction Value CheckWhen selected, Function value check examines the values returned bythe user-supplied objective function, or nonlinear constraint function, andproduces an error if the user-supplied function returns Inf, NaN, orcomplexvalues.Note Function value check does not produce an error for Inf when usedwith fminbnd, fminsearch, orfzero, which handle Inf appropriately.User-Supplied DerivativesSelecting Validate user-supplied derivatives performs an evaluationof the derivatives in the objective and nonlinear constraint functions. Atruntime, a warning message is displayed if the computed and providedderivatives disagree.Jacobian sparsity pattern specifies the sparsity pattern (locations of thenonzeros) of the Jacobian for finite differencing. Given that you provide thissparsity pattern, the solver approximates the Jacobian using sparse finitedifferences. If the structure is unknown, you can set this option to a densematrix (the default value), but note that this can be expensive for largeproblems, so it is best to determine the sparsity structure.Jacobian multiply function specifies the function handle for a multiplyfunction. This function computes Jacobian-matrix products without formingthe Jacobian. Note that this option is only available when the Derivativesfield is set to Jacobian supplied in objective function.Hessian sparsity pattern specifies the sparsity pattern (locations of thenonzeros) of the Hessian for finite differencing. Given that you provide thissparsity pattern, the solver approximates the Hessian using sparse finitedifferences of the gradient. If the structure is unknown, you can set this5-32