A Comparative Analysis of Nature-Inspired Optimization Approaches to 2D Geometric Modelling for Turbomachinery Applications

<table class="table-group" id="tab10"><tr><td><table class="table"><tr><td class="thead-hr" colspan="6"><hr/></td></tr><tr class="thead"><td align="left"> </td><td align="center">Real-coded GA</td><td align="center">Binary GA</td><td align="center">DE</td><td align="center">PSO</td><td align="center">IWO</td></tr><tr><td class="thead-hr" colspan="6"><hr/></td></tr><tr><td align="left">CPU time (Sec)</td><td align="center">240</td><td align="center">218</td><td align="center">216</td><td align="center">14</td><td align="center">23</td></tr><tr class="table-tr"><td colspan="6"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

Computational efficiency (average of 30 runs).

Mathematical Problems in Engineering

tab10

Table 10

Table 10: A Comparative Analysis of Nature-Inspired Optimization Approaches to 2D Geometric Modelling for Turbomachinery Applications 