GOT-It: General Optimization Tool – Innovative Technology
Optimization means to determine the best elements of a set (the optimum) in terms of a given quantitative criteria.
Example : to minimize the losses in a device, to reduce the response time of an actuator, etc.
Boost your Magsoft simulation tool capacities
The GOT-It optimization software comes on board to complement Magsoft modelling tools (Flux, InCa3D, Portunus) and offers the ability to boost their capabilities to define the best device configuration(s) according to a set of constrain.
A powerful and reliable tool
Based on modern mathematical optimization methods, GOT-It’s powerful solver is based on advanced algorithms initially developed by the G2Elab. These algorithms were developed from the beginning in the Magsoft « software philosophy ».
A full range of optimization algorithms (genetic, conjugate gradient, simulated annealing …) enable the user to select the best method in order to optimize his application case.
Optimize without being an expert in mathematics!
Cases of optimization from various applications are now accessible for everyone thanks to a user friendly interface, including interactive commands. The user has access to the most advanced optimization functions. He simply has to enter the parameters, constraint and values to optimize. From this data, GOT-It will define the best configuration(s).
The challenge of computing time reduction
An efficient optimization tool is a software which reduces the computing time to a minimum with the guarantee of accurate results. From the beginning, GOT-It was developed to solve large complicated problems. Therefore, it supplies efficient tools for model reduction and enables indirect optimization in a very simple way.
Very efficient with finite elements models
Using GOT-It enables working on cases which could not be considered up to now.
- Mono or multi-objectives optimization, with or without constraints
- Direct or indirect optimization
- Stochastic and Determinist Algorithms
- Global optimum searching
- Robustness analysis