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<p class="MsoPlainText" style="margin-left:70.8pt"><span lang="EN-US">Dear colleagues,<o:p></o:p></span></p>
<p class="MsoPlainText" style="margin-left:70.8pt"><span lang="EN-US"><o:p> </o:p></span></p>
<p class="MsoPlainText" style="margin-left:70.8pt"><span lang="EN-US">We have the pleasure to announce the publication of the book ”Guided Randomness in Optimization”, by Maurice CLERC:
<o:p></o:p></span></p>
<p class="MsoPlainText" style="margin-left:70.8pt"><span lang="EN-US"><o:p> </o:p></span></p>
<p class="MsoPlainText" style="margin-left:70.8pt"><span style="mso-fareast-language:FR"><img width="187" height="297" id="Image_x0020_1" src="cid:image003.png@01D0AD1D.493CC2C0" alt="cid:D6CBD6F6-3638-4F24-9CC5-598D71791C0A"></span><o:p></o:p></p>
<p class="MsoPlainText" style="margin-left:70.8pt"><o:p> </o:p></p>
<p class="MsoPlainText" style="margin-left:70.8pt"><o:p> </o:p></p>
<p class="MsoPlainText" style="margin-left:70.8pt"><span lang="EN-US">This book is the first to appear in the Metaheuristics series (Wiley-ISTE), coordinated by Nicolas Monmarché and Patrick Siarry.<o:p></o:p></span></p>
<p class="MsoPlainText" style="margin-left:70.8pt"><span lang="EN-US"><o:p> </o:p></span></p>
<p class="MsoPlainText" style="margin-left:70.8pt">Optimization metaheuristics draw at random to make certain choices or apply certain rules. In order to do this, they need to use one or several random number generators (RNG). Many kinds of RNGs exist, from
the true random ones to the simple coded ones. <span lang="EN-US">They can be manipulated to produce specific distributions. The performances of an algorithm are dependent on the RNGs that are used.
<o:p></o:p></span></p>
<p class="MsoPlainText" style="margin-left:70.8pt"><o:p> </o:p></p>
<p class="MsoPlainText" style="margin-left:70.8pt"><span lang="EN-US">This book is interested in a comparison with optimizers.
</span>It defines an effort-result approach, from which all classical criteria can be derived (median, mean, etc.), as well as some other more sophisticated criteria.<o:p></o:p></p>
<p class="MsoPlainText" style="margin-left:70.8pt"><span lang="EN-US">The appendices contain all the source codes (Scilab) that have been used for the examples and figures, a recapitulation of the most frequent errors, and a reflection on unnecessary randomness,
which briefly explains why and how the stochastic aspect of the optimization could be avoided in certain cases.<o:p></o:p></span></p>
<p class="MsoPlainText" style="margin-left:70.8pt"><span lang="EN-US"><o:p> </o:p></span></p>
<p class="MsoPlainText" style="margin-left:70.8pt"><span lang="EN-US">Wiley-ISTE Editions - 316 pages - May 2015
<o:p></o:p></span></p>
<p class="MsoPlainText" style="margin-left:70.8pt"><a href="http://eu.wiley.com/WileyCDA/WileyTitle/productCd-1848218052.html"><span style="color:windowtext;text-decoration:none">http://eu.wiley.com/WileyCDA/WileyTitle/productCd-1848218052.html</span></a><o:p></o:p></p>
<p class="MsoPlainText" style="margin-left:70.8pt"><o:p> </o:p></p>
<p class="MsoPlainText" style="margin-left:70.8pt"><o:p> </o:p></p>
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