Main

## Julia Optimization Package

## Main.JuliaOpt History

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### Download APM Julia Library and Example Problem

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### Download APM Julia Library

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APM Julia is designed for large-scale optimization and accesses solvers of constrained, unconstrained, continuous, and discrete problems. Problems in linear programming, quadratic programming, integer programming, nonlinear optimization, systems of dynamic nonlinear equations, and multiobjective optimization can be solved. The platform can find optimal solutions, perform tradeoff analyses, balance multiple design alternatives, and incorporate optimization methods into external modeling and analysis software. It is free for academic and commercial use. Example applications of nonlinear models with differential and algebraic equations are available for download below or from the following GitHub repository.

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APM Julia is designed for large-scale optimization and accesses solvers of constrained, unconstrained, continuous, and discrete problems. Problems in linear programming, quadratic programming, integer programming, nonlinear optimization, systems of dynamic nonlinear equations, and multiobjective optimization can be solved. The platform can find optimal solutions, perform tradeoff analyses, balance multiple design alternatives, and incorporate optimization methods into external modeling and analysis software. It is free for academic and commercial use. Example applications of nonlinear models with differential and algebraic equations are available for download below or from the following GitHub repository.

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APM Python with Demo Applications on GitHub

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APM Julia on GitHub

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(:title Julia Optimization Package:) (:keywords nonlinear, Julia, model, predictive control, APMonitor, differential, algebraic, modeling language:) (:description APM Julia: A comprehensive modeling and nonlinear optimization solution with Julia:)

APM Julia is designed for large-scale optimization and accesses solvers of constrained, unconstrained, continuous, and discrete problems. Problems in linear programming, quadratic programming, integer programming, nonlinear optimization, systems of dynamic nonlinear equations, and multiobjective optimization can be solved. The platform can find optimal solutions, perform tradeoff analyses, balance multiple design alternatives, and incorporate optimization methods into external modeling and analysis software. It is free for academic and commercial use. Example applications of nonlinear models with differential and algebraic equations are available for download below or from the following GitHub repository.

git clone git://github.com/APMonitor/apm_julia

APM Python with Demo Applications on GitHub

### Download APM Julia Library and Example Problem

Download APM Julia (version 0.7.1) - Released 16 July 2015

The development roadmap for this and other libraries are detailed in the release notes. The zipped archive contains the APM Julia library **apm.jl** and an example problem for Mixed Integer Nonlinear Programming (MINLP).