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

<table class="algorithm-group"><tr><td><table class="algorithm" id="alg1"><tr><td>(1)</td><td>s0 = GenerateInitialSolution</td></tr><tr><td>(2)</td><td>s∗ = ImprovementStage(s0)</td></tr><tr><td>(3)</td><td>while !StopCondition() do</td></tr><tr><td>(4)</td><td> s' = SimpleRandomPerturbation(s∗)</td></tr><tr><td>(5)</td><td> s∗' = ImprovementStage(s')</td></tr><tr><td>(6)</td><td> if f(s∗') &lt; f(s∗) then</td></tr><tr><td>(7)</td><td>  s∗ = s∗'</td></tr><tr><td>(8)</td><td> end if</td></tr><tr><td>(9)</td><td>end while</td></tr><tr><td>(10)</td><td>return s∗</td></tr></table></td></tr></table>

<div>High-level iterated local search (ILS).</div>

Complexity

alg1

Algorithm 1

Algorithm 1: A Methodology to Determine the Subset of Heuristics for Hyperheuristics through Metalearning for Solving Graph Coloring and Capacitated Vehicle Routing Problems 

Algorithm 1 | A Methodology to Determine the Subset of Heuristics for Hyperheuristics through Metalearning for Solving Graph Coloring and Capacitated Vehicle Routing Problems 