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<li class="navelem"><a class="el" href="namespace_quant_lib.html">QuantLib</a></li><li class="navelem"><a class="el" href="class_quant_lib_1_1_differential_evolution.html">DifferentialEvolution</a></li> </ul>
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<a href="#pub-types">Public Types</a> |
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<div class="title">DifferentialEvolution Class Reference<div class="ingroups"><a class="el" href="group__math.html">Math tools</a> » <a class="el" href="group__optimizers.html">Optimizers</a></div></div> </div>
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<p>Differential Evolution configuration object.
<a href="class_quant_lib_1_1_differential_evolution.html#details">More...</a></p>
<p><code>#include <ql/math/optimization/differentialevolution.hpp></code></p>
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<img id="dynsection-0-trigger" src="closed.png" alt="+"/> Inheritance diagram for DifferentialEvolution:</div>
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<area shape="rect" title="Differential Evolution configuration object." alt="" coords="5,80,144,107"/>
<area shape="rect" href="class_quant_lib_1_1_optimization_method.html" title="Abstract class for constrained optimization method." alt="" coords="5,5,144,32"/>
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Public Types</h2></td></tr>
<tr class="memitem:acf7192c608527efb8f8dedf0a3f2e706"><td class="memItemLeft" align="right" valign="top"><a id="acf7192c608527efb8f8dedf0a3f2e706"></a>enum  </td><td class="memItemRight" valign="bottom"><b>Strategy</b> { <br />
  <b>Rand1Standard</b>,
<b>BestMemberWithJitter</b>,
<b>CurrentToBest2Diffs</b>,
<b>Rand1DiffWithPerVectorDither</b>,
<br />
  <b>Rand1DiffWithDither</b>,
<b>EitherOrWithOptimalRecombination</b>,
<b>Rand1SelfadaptiveWithRotation</b>
<br />
}</td></tr>
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<tr class="memitem:ac52d546ccaf78f582c8099dbd7f2c8af"><td class="memItemLeft" align="right" valign="top"><a id="ac52d546ccaf78f582c8099dbd7f2c8af"></a>enum  </td><td class="memItemRight" valign="bottom"><b>CrossoverType</b> { <b>Normal</b>,
<b>Binomial</b>,
<b>Exponential</b>
}</td></tr>
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Public Member Functions</h2></td></tr>
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 </td><td class="memItemRight" valign="bottom"><b>DifferentialEvolution</b> (const Configuration &configuration=Configuration())</td></tr>
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virtual EndCriteria::Type </td><td class="memItemRight" valign="bottom"><a class="el" href="class_quant_lib_1_1_differential_evolution.html#af885d4fbc08a5499481be168e27dfd0c">minimize</a> (<a class="el" href="class_quant_lib_1_1_problem.html">Problem</a> &p, const <a class="el" href="class_quant_lib_1_1_end_criteria.html">EndCriteria</a> &endCriteria)</td></tr>
<tr class="memdesc:af885d4fbc08a5499481be168e27dfd0c"><td class="mdescLeft"> </td><td class="mdescRight">minimize the optimization problem P <br /></td></tr>
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<tr class="memitem:a0d1470852a558d0194ac7880d477ce9d"><td class="memItemLeft" align="right" valign="top"><a id="a0d1470852a558d0194ac7880d477ce9d"></a>
const Configuration & </td><td class="memItemRight" valign="bottom"><b>configuration</b> () const</td></tr>
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<a name="details" id="details"></a><h2 class="groupheader">Detailed Description</h2>
<div class="textblock"><p>Differential Evolution configuration object. </p>
<p>The algorithm and strategy names are taken from here:</p>
<p>Price, K., Storn, R., 1997. Differential Evolution - A Simple and Efficient Heuristic for Global Optimization over Continuous Spaces. Journal of Global Optimization, Kluwer Academic Publishers, 1997, Vol. 11, pp. 341 - 359.</p>
<p>There are seven basic strategies for creating mutant population currently implemented. Three basic crossover types are also available.</p>
<p>Future development: 1) base element type to be extracted 2) L differences to be used instead of fixed number 3) various weights distributions for the differences (dither etc.) 4) printFullInfo parameter usage to track the algorithm</p>
<dl class="caveats"><dt><b><a class="el" href="caveats.html#_caveats000101">Warning:</a></b></dt><dd>This was reported to fail tests on Mac OS X 10.8.4. </dd></dl>
<p>OptimizationMethod using Differential Evolution algorithm </p>
<dl class="section examples"><dt>Examples</dt><dd><a class="el" href="_global_optimizer_8cpp-example.html#_a22">GlobalOptimizer.cpp</a>.</dd>
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