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</script> <div class="portlet" id="yw0"> <div class="portlet-decoration"> <div class="portlet-title"><i class="icon icon-tasks"></i> Conference Information</div> </div> <div class="portlet-content"> <div align="center"> <h5>EvoCOP 2025: European Conference on Evolutionary Computation in Combinatorial Optimisation</h5> <a href="https://www.evostar.org/2025/evocop/">https://www.evostar.org/2025/evocop/</a> <br /> <table border="0" align="center" cellpadding="0" cellspacing="1"> <tr> <td width="150" height="25"><div align="center">Submission Date:</div></td> <td width="150"><div align="center">2024-11-01</div></td> </tr> <tr> <td width="150" height="25"><div align="center">Notification Date:</div></td> <td width="150"><div align="center">2025-01-10</div></td> </tr> <tr> <td width="150" height="25"><div align="center">Conference Date:</div></td> <td width="150"><div align="center">2025-04-23</div></td> </tr> <tr> <td width="150" height="25"><div align="center">Location:</div></td> <td width="150"><div align="center">Trieste, Italy</div></td> </tr> <tr> <td width="100" height="25"><div align="center">Years:</div></td> <td width="150"><div align="center"><span class="badge badge-info">25</span></div></td> </tr> </table> <div class="hidden-phone" align="center"> QUALIS: <span class="badge badge-warning">b2</span>   Viewed: <span class="badge badge-success">13173</span>   Tracked: <span class="badge badge-warning">2</span>   Attend: <span class="badge badge-important">0</span> </div> </div> <br /> </div> </div> <div class="portlet" id="yw1"> <div class="portlet-decoration"> <div class="portlet-title"><i class="icon icon-bullhorn"></i> Call For Papers</div> </div> <div class="portlet-content"> <pre>Areas of Interest and Contributions EvoCOP welcomes submissions in all experimental and theoretical aspects of evolutionary computation and other metaheuristics to combinatorial optimisation problems, including (but not limited to) the following areas: Applications of metaheuristics to combinatorial optimization problems Theoretical developments Neighbourhoods and efficient algorithms for searching them Variation operators for stochastic search methods Constraint-handling techniques Parallelisation and grid computing Search space and landscape analyses Comparisons between different (also exact) methods Automatic algorithm configuration and design Prominent examples of metaheuristics include (but are not limited to): Evolutionary algorithms Estimation of distribution algorithms Swarm intelligence methods such as ant colony and particle swarm optimisation Artificial immune systems Local search methods such as simulated annealing, tabu search, variable neighbourhood search, iterated local search, scatter search and path relinking Hybrid methods such as memetic algorithms Matheuristics (hybrids of exact and heuristic methods) Hyper-heuristics and autonomous search Surrogate-model-based methods Notice that, by tradition, continuous/numerical optimisation is *not* part of the topics of interest of EvoCOP. Interested authors might consider submitting to other EvoStar conferences such as EvoApplications.</pre><div class="alert alert-warning"> Last updated by <a href="/researcher/1">Dou Sun</a> in 2024-10-07</div> </div> </div>  <div class="portlet" id="yw2"> <div class="portlet-decoration"> <div class="portlet-title"><i class="icon icon-signal"></i> Acceptance Ratio</div> </div> <div class="portlet-content"> <div class="row-fluid"> <div class="span8"> <div id="placeholder" style="height:240px"></div> <script type="text/javascript"> $(function() { var data = [ ['2001', 74.2], ['2002', 56.3], ['2003', 48.7], ['2004', 26.7], ['2005', 36.4], ['2006', 31.2], ['2007', 25.9], ['2008', 34.8], ['2009', 39.6], ['2011', 52.4], ['2012', 45.8], ['2013', 46], ['2014', 47.6], ['2015', 41.3], ['2016', 38.6], ['2017', 41], ['2018', 32.4], ['2019', 37.8], ['2020', 37.8], ['2021', 33.3], ['2022', 46.4] ]; var ticks = [ ['2001', '2001'], ['2002', '2002'], ['2003', '2003'], ['2004', '2004'], ['2005', '2005'], ['2006', '2006'], ['2007', '2007'], ['2008', '2008'], ['2009', '2009'], ['2011', '2011'], ['2012', '2012'], ['2013', '2013'], ['2014', '2014'], ['2015', '2015'], ['2016', '2016'], ['2017', '2017'], ['2018', '2018'], ['2019', '2019'], ['2020', '2020'], ['2021', '2021'], ['2022', '2022'] ]; $.plot("#placeholder", [ data ], { series: { bars: { show: true, barWidth: 0.6, align: "center" } }, xaxis: { ticks: ticks, tickLength: 0 }, yaxis: { max: 100, tickFormatter: function (v, axis) { return v + "%"; } } }); }); </script> </div> <div class="span4"> <div style="height:240px;overflow:scroll"> <div id="yw3" class="grid-view"> <table class="table table-hover table-striped table-bordered table-condensed"> <thead> <tr> <th id="yw3_c0">Year</th><th id="yw3_c1">Submitted</th><th id="yw3_c2">Accepted</th><th id="yw3_c3">Accepted(%)</th></tr> </thead> <tbody> <tr class="odd"> <td>2022</td><td>28</td><td>13</td><td>46.4%</td></tr> <tr class="even"> <td>2021</td><td>42</td><td>14</td><td>33.3%</td></tr> <tr class="odd"> <td>2020</td><td>37</td><td>14</td><td>37.8%</td></tr> <tr class="even"> <td>2019</td><td>37</td><td>14</td><td>37.8%</td></tr> <tr class="odd"> <td>2018</td><td>37</td><td>12</td><td>32.4%</td></tr> <tr class="even"> <td>2017</td><td>39</td><td>16</td><td>41%</td></tr> <tr class="odd"> <td>2016</td><td>44</td><td>17</td><td>38.6%</td></tr> <tr class="even"> <td>2015</td><td>46</td><td>19</td><td>41.3%</td></tr> <tr class="odd"> <td>2014</td><td>42</td><td>20</td><td>47.6%</td></tr> <tr class="even"> <td>2013</td><td>50</td><td>23</td><td>46%</td></tr> <tr class="odd"> <td>2012</td><td>48</td><td>22</td><td>45.8%</td></tr> <tr class="even"> <td>2011</td><td>42</td><td>22</td><td>52.4%</td></tr> <tr class="odd"> <td>2009</td><td>53</td><td>21</td><td>39.6%</td></tr> <tr class="even"> <td>2008</td><td>69</td><td>24</td><td>34.8%</td></tr> <tr class="odd"> <td>2007</td><td>81</td><td>21</td><td>25.9%</td></tr> <tr class="even"> <td>2006</td><td>77</td><td>24</td><td>31.2%</td></tr> <tr class="odd"> <td>2005</td><td>66</td><td>24</td><td>36.4%</td></tr> <tr class="even"> <td>2004</td><td>86</td><td>23</td><td>26.7%</td></tr> <tr class="odd"> <td>2003</td><td>39</td><td>19</td><td>48.7%</td></tr> <tr class="even"> <td>2002</td><td>32</td><td>18</td><td>56.3%</td></tr> <tr class="odd"> <td>2001</td><td>31</td><td>23</td><td>74.2%</td></tr> </tbody> </table><div class="keys" style="display:none" title="/conference/1349"><span>3892</span><span>3893</span><span>3894</span><span>3895</span><span>3525</span><span>3526</span><span>3299</span><span>3300</span><span>2988</span><span>2525</span><span>2526</span><span>2527</span><span>2528</span><span>2529</span><span>2530</span><span>2712</span><span>2711</span><span>2710</span><span>2709</span><span>2708</span><span>2707</span></div> </div></div> </div> </div> </div> </div> <div class="portlet" id="yw4"> <div class="portlet-decoration"> <div 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