For each option, we give a summary line, a description of the optional parameter and details of constraints.

The summary line contains:

Option names are case-insensitive and must be provided in full; abbreviations are not recognized.

This special keyword is used to reset all optional parameters to their default values, and any random state stored in the array comm will be destroyed.

Any option value given with this keyword will be ignored. This optional parameter cannot be queried or got.

This puts an approximate limit on the number of function calls allowed. The total number of calls made is checked at the top of an internal iteration loop, so it is possible that a few calls more than $\mathit{nf}$ may be made.

Constraint: $\mathit{nf}>0$.

This defines the ‘infinite’ bound $\mathit{infbnd}$ in the definition of the problem constraints. Any upper bound greater than or equal to $\mathit{infbnd}$ will be regarded as $\infty$ (and similarly any lower bound less than or equal to $-\mathit{infbnd}$ will be regarded as $-\infty$).

Constraint: $r_{\max }^{\frac{1}{4}}\le \mathit{infbnd}\le r_{\max }^{\frac{1}{2}}$.

If you want to try to accelerate convergence of e05jb by starting local searches from candidate minima, you will require $\mathit{lcsrch}$ to be $'\mathrm{ON}'$.

Constraint: $\mathit{lcsrch}='\mathrm{ON}'\text{ or }'\mathrm{OFF}'$.

This defines the maximal number of iterations to be used in the trust-region loop of the local-search procedure.

Constraint: $\mathit{loclim}>0$.

The value of $\mathit{loctol}$ is the multiplier used during local searches as a stopping criterion for when the approximated gradient is small, in the sense described in [Local Search].

Constraint: $\mathit{loctol}\ge 2\epsilon$.

These keywords specify the required direction of optimization. Any option value given with these keywords will be ignored.

These options control the echoing of each optional parameter specification as it is supplied. List turns printing on, Nolist turns printing off. The output is sent to the current advisory message unit (as defined by (X04ABF not in this release)).

Any option value given with these keywords will be ignored. This optional parameter cannot be queried or got.

For use with random initialization lists ($\mathbf{iinit}=4$). When set to $'\mathrm{ON}'$, an internally-initialized random state is stored in the array comm for use in subsequent calls to e05jb.

Constraint: $\mathit{repeat}='\mathrm{ON}'\text{ or }'\mathrm{OFF}'$.

Along with the initialization list list, this defines a limit on the number of times the root box will be split along any single coordinate direction. If Local Searches is $'\mathrm{OFF}'$ you may find the default value to be too small.

Constraint: $\mathit{smax}>n_r+2$.

As the default termination criterion, computation stops when the best function value is static for $\mathit{stclim}$ sweeps through levels. This parameter is ignored if you have specified a target value to reach in Target Objective Value.

Constraint: $\mathit{stclim}>0$.

If you have given a target objective value to reach in $\mathit{objval}$ (the value of the optional parameter Target Objective Value), $\mathit{objerr}$ sets your desired relative error (from above if Minimize is set, from below if Maximize is set) between obj and $\mathit{objval}$, as described in [Accuracy]. See also the description of the optional parameter Target Objective Safeguard.

Constraint: $\mathit{objerr}\ge 2\epsilon$.

If you have given a target objective value to reach in $\mathit{objval}$ (the value of the optional parameter Target Objective Value), $\mathit{objsfg}$ sets your desired safeguarded termination tolerance, for when $\mathit{objval}$ is close to zero.

Constraint: $\mathit{objsfg}\ge 2\epsilon$.

This parameter may be set if you wish e05jb to use a specific value as the target function value to reach during the optimization. Setting $\mathit{objval}$ overrides the default termination criterion determined by the optional parameter Static Limit.