VirtualLab Fusion – NEW Optimization Package
With the release of VirtualLab Fusion 2024.1, the Optimization Package has joined the VirtualLab Fusion product family.
- It contains powerful local and global optimization algorithms to design a system according to your merit functions.
- The intuitive and user-friendly interface will guide you through the optimization process.
- Powerful post-processing tools will enable you to understand the development of merit function values during the optimization process.
The New Optimization Package
The new Optimization Package comes with various mathematical optimization algorithms:
- the Nelder-Mead method (also known as Downhill-Simplex) - a fast and estiablished local optimization algorithm.
- the differential evolutionary algorithm - a global optimization algorithm, which can be used in combination with the distributed computing technology provided by VirtualLab Fusion.
Familiar Workflow
Using the same user interface, users of VirtualLab Fusions will become easily familiar with the controls for the configuration.
Optimization Process
The new package includes advanced options for defining and specifying merit functions. The merit function are available predefined or can be even specified using a built-in formula editor.
Post Processing
The Optimization Package also supports various post-process options, such as the calculation of pareto-fronts.
USE CASES
Working with the Optimization Package
Introduction to the VirtualLab Fusion Optimization Package
In this use case we would like to introduce the optimization package and shortly show its capabilities.
Learn more
Optimization Examples
In this use case shows an optimization of an AR moth-eye structure using the VirtualLab Fusion Optimization Package.
