An Efficient Hybrid Approach of Finite Element Method, Artificial Neural Network-Based Multiobjective Genetic Algorithm for Computational Optimization of a Linear Compliant Mechanism of Nanoindentation Tester

<table class="fixed-width table-group" id="tab10"><tr><td><table class="table"><colgroup><col style="width:10.79em"/><col style="width:8.34em"/><col style="width:8.47em"/><col style="width:8.45em"/></colgroup><tr><td class="thead-hr" colspan="4"><hr/></td></tr><tr class="thead"><td class="align_left">Performances</td><td class="align_center">Candidate Point 1</td><td class="align_center">Candidate Point 2</td><td class="align_center">Candidate Point 3</td></tr><tr><td class="thead-hr" colspan="4"><hr/></td></tr><tr><td class="align_left">Equivalent stress (MPa)</td><td class="align_center">140.6496</td><td class="align_center">150.1017</td><td class="align_center">155.1464</td></tr><tr><td class="align_left">Displacement (<i>μ</i>m)</td><td class="align_center">398.5</td><td class="align_center">399.8</td><td class="align_center">399.7</td></tr><tr><td class="align_left">Safety factor</td><td class="align_center">3.5952</td><td class="align_center">3.5285</td><td class="align_center">3.4986</td></tr><tr class="table-tr"><td colspan="4"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

<div>Comparison among potentially optimal performances.</div>

Mathematical Problems in Engineering

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Table 10

Table 10: An Efficient Hybrid Approach of Finite Element Method, Artificial Neural Network-Based Multiobjective Genetic Algorithm for Computational Optimization of a Linear Compliant Mechanism of Nanoindentation Tester 

Table 10 | An Efficient Hybrid Approach of Finite Element Method, Artificial Neural Network-Based Multiobjective Genetic Algorithm for Computational Optimization of a Linear Compliant Mechanism of Nanoindentation Tester 