Optimization Toolbox

Optimization Parameters

This table describes fields in the optimization parameters structure options. You can set values of these fields using the function optimset. The column labeled L, M, B indicates whether the parameter applies to large-scale methods, medium scale methods, or both:

• L - Large-scale methods only
• M - Medium-scale methods only
• B - Both large- and medium-scale methods

See the optimset reference page and the individual function reference pages for information about parameter values and defaults.

Note    Links in this table are to Optimization Toolbox functions. These links are to the corresponding MATLAB optimization functions: fminbnd, fminsearch, fzero, lsqnonneg, optimget, optimset.

Parameter Name	Description	L, M, B	Used by Functions
DerivativeCheck	Compare user-supplied analytic derivatives (gradients or Jacobian) to finite differencing derivatives.	B	fgoalattain, fmincon, fminimax, fminunc, fseminf, fsolve, lsqcurvefit, lsqnonlin
Diagnostics	Display diagnostic information about the function to be minimized or solved.	B	All but fminbnd, fminsearch, fzero, and lsqnonneg
DiffMaxChange	Maximum change in variables for finite-difference derivatives.	M	fgoalattain, fmincon, fminimax, fminunc, fseminf, fsolve, lsqcurvefit, lsqnonlin
DiffMinChange	Minimum change in variables for finite-difference derivatives.	M	fgoalattain, fmincon, fminimax, fminunc, fseminf, fsolve, lsqcurvefit, lsqnonlin
Display	Level of display. 'off' displays no output; 'iter' displays output at each iteration; 'final' displays just the final output; 'notify' displays output only if function does not converge.	B	All. See the individual function reference pages for the values that apply.
GoalsExactAchieve	Number of goals to achieve exactly (do not over- or underachieve).	M	fgoalattain
GradConstr	Gradients for the nonlinear constraints defined by the user.	M	fgoalattain, fmincon, fminimax
GradObj	Gradients for the objective functions defined by the user.	B	fgoalattain, fmincon, fminimax, fminunc, fseminf
Hessian	If 'on', function uses user-defined Hessian or Hessian information (when using HessMult), for the objective function. If 'off', function approximates the Hessian using finite differences.	L	fmincon, fminunc
HessMult	Hessian multiply function defined by the user.	L	fmincon, fminunc, quadprog
HessPattern	Sparsity pattern of the Hessian for finite differencing. The size of the matrix is n-by-n, where n is the number of elements in x0, the starting point.	L	fmincon, fminunc
HessUpdate	Quasi-Newton updating scheme.	M	fminunc
Jacobian	If 'on', function uses user-defined Jacobian or Jacobian information (when using JacobMult), for the objective function. If 'off', function approximates the Jacobian using finite differences.	B	fsolve, lsqcurvefit, lsqnonlin
JacobMult	Jacobian multiply function defined by the user.	L	fsolve, lsqcurvefit, lsqlin, lsqnonlin
JacobPattern	Sparsity pattern of the Jacobian for finite differencing. The size of the matrix is m-by-n, where m is the number of values in the first argument returned by the user-specified function fun, and n is the number of elements in x0, the starting point.	L	fsolve, lsqcurvefit, lsqnonlin
LargeScale	Use large-scale algorithm if possible.	B	fmincon, fminunc, fsolve, linprog, lsqcurvefit, lsqlin, lsqnonlin, quadprog
LevenbergMarquardt	Choose Levenberg-Marquardt over Gauss-Newton algorithm.	M	lsqcurvefit, lsqnonlin
LineSearchType	Line search algorithm choice.	M	fminunc, fsolve, lsqcurvefit, lsqnonlin
MaxFunEvals	Maximum number of function evaluations allowed.	B	fgoalattain, fminbnd, fmincon, fminimax, fminsearch, fminunc, fseminf, fsolve, lsqcurvefit, lsqnonlin
MaxIter	Maximum number of iterations allowed.	B	All but fzero and lsqnonneg
MaxSQPIter	Maximum number of SQP iterations allowed	M	fmincon
MaxPCGIter	Maximum number of PCG iterations allowed.	L	fmincon, fminunc, fsolve, lsqcurvefit, lsqlin, lsqnonlin, quadprog
MeritFunction	Use goal attainment/minimax merit function (multiobjective) vs. fmincon (single objective).	M	fgoalattain, fminimax
MinAbsMax	Number of F(x) to minimize the worst case absolute values	M	fminimax
NonlEqnAlgorithm	Choose Levenberg-Marquardt or Gauss-Newton over the trust-region dogleg algorithm.	M	fsolve
OutputFcn	Specify a user-defined function that the optimization function calls at each iteration. See Output Function.	B	fgoalattain, fmincon, fminimax, fminunc, fseminf, lsqcurvefit, lsqnonlin
PrecondBandWidth	Upper bandwidth of preconditioner for PCG.	L	fmincon, fminunc, fsolve, lsqcurvefit, lsqlin, lsqnonlin, quadprog
Simplex	If 'on', function uses the simplex algorithm.	M	linprog
TolCon	Termination tolerance on the constraint violation.	B	fgoalattain, fmincon, fminimax, fseminf
TolFun	Termination tolerance on the function value.	B	fgoalattain, fmincon, fminimax, fminsearch, fminunc, fseminf, fsolve, linprog (large-scale only), lsqcurvefit, lsqlin (large-scale only), lsqnonlin, quadprog (large-scale only)
TolPCG	Termination tolerance on the PCG iteration.	L	fmincon, fminunc, fsolve, lsqcurvefit, lsqlin, lsqnonlin, quadprog
TolX	Termination tolerance on x.	B	All functions except the medium-scale algorithms for linprog, lsqlin, and quadprog
TypicalX	Typical x values. The length of the vector is equal to the number of elements in x0, the starting point.	L	fmincon, fminunc, fsolve, lsqcurvefit, lsqlin, lsqnonlin, quadprog

Output Arguments

Output Function