# MV- 3010: Optimization Using MotionView - HyperStudy

In this tutorial, you will perform an optimization study in the MotionView - HyperStudy environment and compare the baseline and optimized models.

- hs.mdl
- targeted_toe.csv
- Setup.xml (saved in the tutorial MV-3000: DOE Using MotionView - HyperStudy)
- The nom_run folder created in MV-3000: DOE Using MotionView - HyperStudy)

- Theory
- In general, an optimization problem consists of the following:
- The design constraints.
- The objective function.
- The design variables.

Design variables change during optimization. The design variables always have a certain range within which they can be modified. Typical examples of design variables are thickness of shell elements, shape vectors, and masses.

The changes in the design variables cause some change in model responses. Such responses can become either objective function or design constraints. Examples of such responses include displacements and forces.

The response to be minimized or maximized becomes the objective function, while the rest of the responses that need to be within a certain tolerance range become constraints. Only one response can be defined as objective function.

HyperStudy can be used to set-up and perform an optimization study on a MotionView model. You can also use HyperStudy to perform optimization studies involving both linear and non-linear CAE analysis as well as perform optimization of mathematical equations using Templex. HyperStudy creates the input parameter files using Templex and provides iterative changes to them during the optimization process. HyperStudy uses HyperOpt (a general purpose, wrap around software) as the optimization engine to perform optimization, in conjunction with both linear and non-linear CAE analysis software. HyperOpt uses a robust sequential response surface methodology for optimization.