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<a name = "hj-top"> </a><table class = "table1" id = "table11"><tr><td><table class = "DocHeader"><tr><td class = "DocHeader1" colspan = "2"><h1>Global Stop Condition (Number of Iterations)</h1></td></tr><tr><td class = "DocHeader4" colspan = "2"/></tr><tr><td class = "DocHeader3" colspan = "2"><table class = "DocThemeIntro" id = "table12"><tr><td class = "Intro1Only"><p class = "header"><p class = "abstract">
<span class = "shortdesc"> Generally, the number of optimization cycles should be limited by default to a certain
      number to limit the computation time for optimizations with convergence problems. </span>

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<p> The stop criterion is the maximum number of optimization iterations, which is default 20
    for sensitivity-based and 3 for controller-based optimizations. When the maximum number of
    optimization iterations is reached, the optimization algorithm always stops independent of other
    criteria. The allowed maximum number of optimization iterations can be increased or decreased by
    the user. This is defined by the parameter <code class = "ph codeph">ITER_MAX</code> of the <code class = "ph codeph">STOP</code>
    command.</p>
<pre class = "codeblock">
<code class = "ph codeph">
STOP
 ID_NAME  = global_stop
 ITER_MAX = 5
END_
</code>
</pre>
<p>where <code class = "ph codeph">ITER_MAX</code> is decreased to 5.</p>
<p>A global stop condition is essential to limit the number of design cycles in case no convergence
        is obtained. User-defined stop conditions adapted to the task (instead of using the default
        values) might improve efficiency.</p>
<p>Since a "partially optimized model" can be used as a starting model for a subsequent
        optimization, it makes sense to calculate first a few design cycles and then to use
        information from the optimization result to calculate more design cycles with adjusted
        settings.</p>

<table class = "Remark" id = "table132"><tr><td class = "Remark"><span class = "run-in.important">Important:
				</span><span class = "notecontent">
<ul class = "ul">
<li class = "li"> For simple bead optimization tasks, it is often sufficient to limit the number of iterations to
      15. For more complex setups, the iterations should be increased to around 25, which is enough
      for many cases. However, there are setups where even more iterations are needed and it is hard
      to guess a number that is valid for all cases.</li>
<li class = "li">The global stop criterion leads to a stop of the optimization,  independent of a complete
      convergence of the result. For bead optimization tasks, this is no drawback as the
      optimization task can be continued for some more steps using the input file of the last
      iteration as start file.</li>
</ul>
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