Hybrid Approach of Finite Element Method, Kigring Metamodel, and Multiobjective Genetic Algorithm for Computational Optimization of a Flexure Elbow Joint for Upper-Limb Assistive Device

<table class="fixed-width table-group" id="tab2"><tr><td><table class="table"><colgroup><col style="width:16.84em"/><col style="width:3.53em"/></colgroup><tr><td class="thead-hr" colspan="2"><hr/></td></tr><tr class="thead"><td class="align_left">Parameters</td><td class="align_center">Value</td></tr><tr><td class="thead-hr" colspan="2"><hr/></td></tr><tr><td class="align_left">Number of initial samples</td><td class="align_center">100</td></tr><tr><td class="align_left">Number of samples per iteration</td><td class="align_center">100</td></tr><tr><td class="align_left">Maximum allowable Pareto percentage</td><td class="align_center">70</td></tr><tr><td class="align_left">Convergence stability percentage</td><td class="align_center">2</td></tr><tr><td class="align_left">Maximum number of iterations</td><td class="align_center">20</td></tr><tr><td class="align_left">Maximum number candidates</td><td class="align_center">6</td></tr><tr><td class="align_left">Crossover probability</td><td class="align_center">0.7</td></tr><tr><td class="align_left">Mutation probability</td><td class="align_center">0.01</td></tr><tr class="table-tr"><td colspan="2"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

<div>Controllable parameters for MOGA algorithm.</div>

Complexity

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Table 2

Table 2: Hybrid Approach of Finite Element Method, Kigring Metamodel, and Multiobjective Genetic Algorithm for Computational Optimization of a Flexure Elbow Joint for Upper-Limb Assistive Device 

Table 2 | Hybrid Approach of Finite Element Method, Kigring Metamodel, and Multiobjective Genetic Algorithm for Computational Optimization of a Flexure Elbow Joint for Upper-Limb Assistive Device 