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Description
Artelys Knitro stands out as a premier solver for extensive nonlinear optimization challenges, providing a comprehensive array of sophisticated algorithms and functionalities to tackle intricate issues across multiple sectors. It boasts four cutting-edge algorithms: two based on interior-point/barrier techniques and two utilizing active-set/sequential quadratic programming methods, which facilitate both efficient and reliable resolutions for diverse optimization scenarios. Furthermore, Knitro features three dedicated algorithms for mixed-integer nonlinear programming, leveraging heuristics, cutting planes, and branching rules to adeptly manage discrete variables. Among its notable capabilities, Knitro includes parallel multi-start functionalities for global optimization, automatic and parallel adjustments of option settings, and intelligent initialization approaches aimed at swiftly identifying infeasibility. The solver is compatible with various programming environments, offering object-oriented APIs for languages such as C++, C#, Java, and Python, thus ensuring versatility for developers. Additionally, its robust support for parallel computing enhances performance and scalability for large-scale applications.
Description
MPCPy is a Python library designed to support the testing and execution of occupant-integrated model predictive control (MPC) within building systems. This tool emphasizes the application of data-driven, simplified physical or statistical models to forecast building performance and enhance control strategies. It comprises four primary modules that provide object classes for data importation, interaction with real or simulated systems, data-driven model estimation and validation, and optimization of control inputs. Although MPCPy serves as a platform for integration, it depends on various free, open-source third-party software for model execution, simulation, parameter estimation techniques, and optimization solvers. This encompasses Python libraries for scripting and data manipulation, along with more specialized software solutions tailored for distinct tasks. Notably, the modeling and optimization tasks related to physical systems are currently grounded in the specifications of the Modelica language, which enhances the flexibility and capability of the package. In essence, MPCPy enables users to leverage advanced modeling techniques through a versatile and collaborative environment.
API Access
Has API
API Access
Has API
Integrations
Python
AIMMS
AMPL
C#
C++
GAMS
Java
Julia
MATLAB
Microsoft Excel
Integrations
Python
AIMMS
AMPL
C#
C++
GAMS
Java
Julia
MATLAB
Microsoft Excel
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
Free
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Artelys
Founded
2000
Country
France
Website
www.artelys.com/solvers/knitro/
Vendor Details
Company Name
MPCPy
Country
United States
Website
github.com/lbl-srg/MPCPy