An In-depth Benchmarking of Evolutionary and Swarm Intelligence Algorithms for Autoscaling Parameter Sweep Applications on Public Clouds

<table class="table-group" id="tab4"><tr><td><table class="table"><tr><td class="thead-hr" colspan="2"><hr/></td></tr><tr class="thead"><td class="align_left">Parameter</td><td class="align_center">Value</td></tr><tr><td class="thead-hr" colspan="2"><hr/></td></tr><tr><td class="align_left">Population size</td><td class="align_center">92</td></tr><tr><td class="align_left">Number of reference points</td><td class="align_center">91</td></tr><tr><td class="align_left">Number of evaluations</td><td class="align_center">36800</td></tr><tr><td class="align_left">Pc</td><td class="align_center">1</td></tr><tr><td class="align_left">Dc</td><td class="align_center">30</td></tr><tr><td class="align_left">Pm</td><td class="align_center">1/15 (the length of each encoded solution is 15)</td></tr><tr><td class="align_left">Dm</td><td class="align_center">20</td></tr><tr class="table-tr"><td colspan="2"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

<div>Configuration for NSGA-III and E-NSGA-III</div>

Scientific Programming

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Table 4

Table 4: An In-depth Benchmarking of Evolutionary and Swarm Intelligence Algorithms for Autoscaling Parameter Sweep Applications on Public Clouds 