Meet Artelys at the 2019 INFORMS Annual Meeting in Seattle (USA)
The INFORMS Annual Meeting brings together more than 6,000 INFORMS members constituted of top industrials and academics in analytics.
Artelys will be at booth 15. Come meet our consultants, they will be happy to provide you with information on our products, consulting services and training, and discuss the latest news in the advanced analytics field.
During the event, Artelys will present the latest version of its nonlinear optimization solver Artelys Knitro (version 12.0), and especially its brand-new interface with Julia/JuMP.
Details:
- Monday, October 21, 8:00 – 8:45: Nonlinear Optimization Using Artelys Knitro with Julia/JuMP presented by Richard Waltz, Lead Developer of Artelys Knitro
Artelys Knitro 16.0: Model Nonlinear Problems Natively, Solve Them Concurrently
Artelys is pleased to announce the release of Knitro 16.0, a major version introducing two flagship features — a native Nonlinear Modeler and a Concurrent Solver — alongside significant performance and robustness improvements for nonlinear, mixed-integer and linear optimization problems.
First Successful Auction for the New French Capacity Mechanism!
— The first auction of the new French Capacity Mechanism was successfully held on Monday, 6 July 2026. Artelys is proud to provide the market clearing algorithm used to select the accepted capacity offers.
Artelys compared the compensation mechanisms available for hydropower across global electricity markets in collaboration with CEATI
— Artelys is proud to have issued a new report published by CEATI, providing a comprehensive benchmark of compensation mechanisms available to hydropower assets across electricity markets in North America, Europe, and beyond.
Artelys Crystal HPC: Our integrated, sovereign High-Performance Computing (HPC) managed platform for industries
— Organizations that run complex simulations, large-scale optimizations, or sensitive calculations face a threefold challenge: securing the computing power to match their ambitions, ensuring data sovereignty, and avoiding weeks of setup time before seeing initial results.
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