Artelys Knitro

What is Artelys Knitro ?

The most advanced solver for nonlinear optimization

Nonlinear optimization issues arise in numerous commercial and industrial applications: portfolio optimization, optimal power flow, predictive control of nonlinear model, Nash equilibrium problems. To solve these problems customers around the world rely on Artelys Knitro for its efficiency and robustness.

Resolved Problem Classes

Artelys Knitro specializes in solving large-scale nonlinear mathematical problems. It is the only nonlinear solver with seven different algorithms, allowing you to solve a wide variety of complex optimization problems.

General nonlinear problems (NLP), including non-convex

Systems of nonlinear equations

• Linear problems (LP)
• Quadratic problems (QP / QCQP), convex and non-convex
• Second-order cone programs (SOCP), including nonlinear restrictions and objectives
• Least squares / linear and nonlinear regression problems
• Mathematical programs with complementarity restrictions (MPCC / MPEC)
• Mixed whole nonlinear problems (MIP / MINLP)
• Derivative-free optimization (DFO) issues

Applications

Artelys Knitro is currently used in many application areas, thus demonstrating its versatility. From fundamental mathematics to sustainable development, Artelys Knitro has been found useful by a wide variety of Operational Research professionals.

• Financial and banking
• Computational economics and game theory
• Statistics and data analysis
• Energy
• Sustainable development
• Great control and dynamic optimization
• Telecommunications
• Optics and spectroscopy
• Mathematics and geometry

Main Features

The optimization techniques used by Artelys Knitro offer the main combination of efficiency and computational robustness. Thanks to several important features, Artelys Knitro can efficiently solve a wide range of optimization problems.

• Efficient and robust solution to large-scale problems
• Two inner point/barrier algorithms and two active sets /SQP
• Three algorithms for mixed whole nonlinear optimization
• Heuristics, cutting plans, branching rules for MINLP
• Special routine for dealing with complementary constraints
• Parallel multipart feature for global optimization
• Ability to run multiple algorithms simultaneously
• Automatic and parallel adjustment of option settings
• Approximate first-order automatic calculation and second-order derivatives
• Intelligent infection start-up and rapid detection strategies

System Requirements

Windows 64-bit 

Windows Server 2008, Vista, Windows 7, Windows 8, Windows 8.1, Windows 10

Linux 64-bit 

RedHat compatible (glibc2.5+) (parallel features require OpenMP)

Mac OS X 64-bit

Version 10.8 (Mountain Lion) or later