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
Download APM Julia Library
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).