Artelys Knitro 10.3: support for Python 3 and improved performance!
From a numerical perspective, large speedups are to be seen on some classes of ill-conditioned models. This is due to new preconditioning techniques applied to the subproblems solved by conjugate gradient method in the Knitro interior-point/barrier algorithms. Furthermore, Artelys Knitro 10.3 offers several improvements to the internal linear algebra and linear solvers used internally for better robustness and efficiency.
Additional features:
• Significant improvements in large-scale least-squares models, solving the instances 10 times faster!
• Improvements in the “feasibility restoration phase” used when Knitro is struggling to get feasible allowing faster detection of infeasible models.
• Overall efficiency and robustness improvements on general nonlinear models as well as significant improvements in efficiency on models with integer variables.
Artelys continues to expand internationally
With over 20 years of experience in mathematical optimization, Artelys offers a wide range of advanced components to adapt to your most complex challenges on an international scale.
Analysis of the environmental impact of renewable energies
— The study carried out by Artelys highlights the benefits of renewable energies in the fight against climate change. The analysis also looks at other major issues, such as biodiversity, the use of raw materials and the reduction of pollution.
Join us at the METIS 3 dissemination event organized by Artelys!
— Artelys is thrilled to invite you to the METIS 3 Dissemination Event taking place on 17 April. During this online event, we will present the latest results of the METIS project and discuss the benefits of using advanced multi-energy modelling solutions such as METIS for energy and climate policymaking.
Artelys Knitro 14: new release of our nonlinear optimization solver
— 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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