A Methodology to Determine the Subset of Heuristics for Hyperheuristics through Metalearning for Solving Graph Coloring and Capacitated Vehicle Routing Problems

<table class="table-group" id="tab13"><tr><td><table class="table"><tr><td class="thead-hr" colspan="3"><hr/></td></tr><tr><td class="align_left">Correctly classified</td><td class="align_center">114</td><td class="align_center">91.20%</td></tr><tr><td class="align_left">Incorrectly classified</td><td class="align_center">11</td><td class="align_center">8.80%</td></tr><tr><td class="align_left">TP rate</td><td class="align_center">0.912</td><td class="align_center"> </td></tr><tr><td class="align_left">FP rate</td><td class="align_center">0.022</td><td class="align_center"> </td></tr><tr><td class="align_left">Precision</td><td class="align_center">0.918</td><td class="align_center"> </td></tr><tr><td class="align_left">Recall</td><td class="align_center">0.912</td><td class="align_center"> </td></tr><tr class="table-tr"><td colspan="3"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

Complexity

tab13

Table 13

Table 13: A Methodology to Determine the Subset of Heuristics for Hyperheuristics through Metalearning for Solving Graph Coloring and Capacitated Vehicle Routing Problems 

Table 13 | A Methodology to Determine the Subset of Heuristics for Hyperheuristics through Metalearning for Solving Graph Coloring and Capacitated Vehicle Routing Problems 