An Automated Structural Optimisation Methodology for Scissor Structures Using a Genetic Algorithm

<table class="figure-group"><tr class="fig-image" id="a"><td><object data="https://static.hindawi.com/articles/acisc/volume-2017/6843574/figures/6843574.fig.009a.svgz" name="6843574.fig.009a" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(a) </b>Generational distance</td></tr><tr class="fig-image" id="b"><td><object data="https://static.hindawi.com/articles/acisc/volume-2017/6843574/figures/6843574.fig.009b.svgz" name="6843574.fig.009b" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(b) </b>Hypervolume</td></tr><tr class="fig-image" id="c"><td><object data="https://static.hindawi.com/articles/acisc/volume-2017/6843574/figures/6843574.fig.009c.svgz" name="6843574.fig.009c" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(c) </b>Rate of feasible solutions</td></tr><tr class="fig-image" id="d"><td><object data="https://static.hindawi.com/articles/acisc/volume-2017/6843574/figures/6843574.fig.009d.svgz" name="6843574.fig.009d" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(d) </b>Hypervolume for generations 3 (0.7668) and 16 (1.4978)</td></tr></table>

<div>While the GD is dropping with the generations, the HR is rising and the RF is fluctuating. This means that as the generations progress, the Pareto fronts are coming closer to each other and their extent is becoming bigger while procuring enough solutions that are failing.</div>

Applied Computational Intelligence and Soft Computing

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Figure 9

Figure 9: An Automated Structural Optimisation Methodology for Scissor Structures Using a Genetic Algorithm 