Artelys Knitro 12.4 further improves the interface versatility
This release does not only come with performance improvements, in particular for general nonlinear problems, but also with improvements of the interface:
- Improvement on NLP:
- New dynamic scaling of the limited-memory Quasi-Newton BFGS, more robust and efficient for all algorithms. This leads to an average performance improvement of 20% on general nonlinear instances when using this Hessian approximation.
- New Knitro API functions:
- Allow deleting or changing linear or constant structures of a problem and then re-solving.
- Allow to retrieve information about the feasibility of the variables and constraints after both the presolve and solving process, giving a detailed analysis of the complex infeasibilities in nonlinear problems.
- Allow users to provide their own customized linear algebra solver, which is useful when the problem has a very specific structure and can be solved with highly specialized routines. This feature was recently applied with success to an industrial problem and enabled a 2x overall speedup.
In addition, Artelys Knitro 12.4 brings:
- Improvement on MINLP:
- Improved heuristics strategies
- Early integer-feasible solution found on 15% more instances
- Newly supported platforms:
- Support for the new Apple M1 chip
Knitro 14.2 solve your toughest nonlinear non-convex models in seconds
— We are pleased to announce that Artelys Knitro 14.0 is now available! This new version enables compagnies to solve complex non-linear optimization problems with unprecedented efficency and precision.
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Driving Renewable Energy Integration: Advanced Solutions to increase the existing power grid’s renewable hosting capacity
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As part of the Horizon Europe program, Artelys is participating in the HyNet project. This initiative aims to study and optimize the operation of hybrid AC/DC power grids in the context of the rapid growth of power electronics-based technologies and the widespread deployment of distributed energy resources.
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