# HS-4000: Optimization Method Comparison: Arm Model Shape Optimization

Learn how to perform an Optimization and compare different methods for efficiency and effectiveness.

- Volume = 1.77E+06 mm3
- Max_Disp = 1.41 mm
- Max_Stress = 195.29 MPa

In this tutorial, the Optimization objective is to reduce Volume, while respecting a constraint on Max_Disp that should be less than 1.5 mm.

In HS-3000: Fit Method Comparison - Approximation on the Arm Model, you learned that it was difficult to accurately capture the Max_Stress function using a Fit approximation. In the DOE analysis, you learned that most of the tested design configurations for Max_Stress were below 300 MPa. For these reasons, you will not consider a constraint on the Max_Stress function. Max_Stress values can be collected throughout the Optimization when running the exact solver.

## ARSM, Six Input Variables, Exact Solver

## ARSM, Nine Input Variables, Exact Solver

## GRSM, Six Input Variables, Exact Solver

## SQP, Six Input Variables, Exact Solver

## SQP, Six Input Variables, RBF_MELS

## GA, Six Input Variables, RBF_MELS

## Optimization Methods Comparison

Optimization Method | # of Evaluations | Volume Objective |
---|---|---|

ARSM, 9 IVs, Exact Solver | 14 | 1702450.0 |

ARSM, 6 IVs, Exact Solver | 11 | 1703330.0 |

GRSM, 6 IVs, Exact Solver | 50 (22nd is the optimum) | 1652830.0 |

SQP, 6 IVs, Exact Solver | 179 | 1659730.0 |

SQP, 6 IVs, Fit | - | 1666990.6 |

GA, 6 IVs, Fit | - | 1665387.3 |

## Reliability-Based Design Optimization Study

In this step, run a reliability based design optimization study.

This topic will be discussed in HS-5000: Stochastic Method Comparison: Stochastic Study of the Arm Model

## Multi-Objective Optimization Study

In this step, you will run a multi-objective optimization study.

This topic will be discussed in HS-4425: Multi-Objective Shape Optimization Study.