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.
Exponential speedups on selected nonlinear least square instance
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 Announces Major New Release of Artelys Crystal Super Grid
Artelys is thrilled to announce a new major release of Artelys Crystal Super Grid.
Artelys Canada joins IVADO to catalyze innovation in optimization and digital intelligence
We are pleased to announce that Artelys Canada has joined the IVADO community as an industrial member, marking the beginning of a new strategic partnership.
Artelys Knitro 15.1: Solve your toughest pooling applications!
Artelys releases Knitro 15.1, bringing a new wave of performance upgrades and usability improvements to help you solve large-scale optimization problems faster than ever.
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