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
Artelys Introduces Future Sight: a Visualisation Tool Supporting the Energy Transition
As partner in the European Climate + Energy Modeling Forum (ECEMF) – a Horizon 2020 Europe project uniting research institutes and leading energy modellers in Europe – Artelys has contributed to modeling activities powered by Artelys Crystal Super Grid modelisation tool, and has led the development of a fully-fledged visualisation tool.  
Supercharging Optimisation: How Artelys, FICO and NVIDIA cuOpt Join Efforts to Scale Up Energy System Optimisation
As energy system models continue to scale—reaching up to hundreds of millions of variables and constraints—traditional CPU-based optimisation solvers are hitting performance and memory bottlenecks. These increasingly complex models are essential for planning Europe’s energy transition, yet solving them within realistic timeframes has become a pressing challenge.
Artelys is powering SEleNe CC’s Common Grid Model (CGM) Service
Artelys provides maintenance and support services of the calculation module used to perform the European Merging Function (EMF) at SEleNe CC
Improving electrical transformer production planning with artificial intelligence solutions
Improving high-voltage transformer production planning at the Hitachi Energy factory in Varennes with advanced artificial intelligence solutions.
subscribe to our newsletters
© ARTELYS document.write(new Date().getFullYear()); • All rights reserved • Legal mentions