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<a name="A-simulated-annealing-_0028stochastic_0029-optimizer"></a>
<h3 class="section">1.17 A simulated annealing (stochastic) optimizer</h3>
<a name="index-samin"></a>
<p>This simulated annealing algorithm implicitely honours bound
constraints.
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<a name="Helptext_003a-6"></a>
<h4 class="subheading">Helptext:</h4>
<a name="XREFsamin"></a><pre class="verbatim">samin: simulated annealing minimization of a function. See samin_example.m
usage: [x, obj, convergence, details] = samin("f", {args}, {control})
Arguments:
* "f": function name (string)
* {args}: a cell array that holds all arguments of the function,
* {control}: a cell array with 11 elements
* LB - vector of lower bounds
* UB - vector of upper bounds
* nt - integer: # of iterations between temperature reductions
* ns - integer: # of iterations between bounds adjustments
* rt - (0 < rt <1): temperature reduction factor
* maxevals - integer: limit on function evaluations
* neps - integer: number of values final result is compared to
* functol - (> 0): the required tolerance level for function value
comparisons
* paramtol - (> 0): the required tolerance level for parameters
* verbosity - scalar: 0, 1, or 2.
* 0 = no screen output
* 1 = only final results to screen
* 2 = summary every temperature change
* minarg - integer: which of function args is minimization over?
Returns:
* x: the minimizer
* obj: the value of f() at x
* convergence:
0 if no convergence within maxevals function evaluations
1 if normal convergence to a point interior to the parameter space
2 if convergence to point very near bounds of parameter space
(suggest re-running with looser bounds)
* details: a px3 matrix. p is the number of times improvements were found.
The columns record information at the time an improvement was found
* first: cumulative number of function evaluations
* second: temperature
* third: function value
Example: see samin_example
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