APMonitor Optimization Suite

The APMonitor Modeling Language is optimization software for mixed-integer and differential algebraic equations. It is coupled with large-scale solvers for linear, quadratic, nonlinear, and mixed integer programming (LP, QP, NLP, MILP, MINLP). Modes of operation include data reconciliation, real-time optimization, dynamic simulation, and nonlinear predictive control. It is available through MATLAB, Python, or from a web browser interface.

Solve Optimization Problems
Browse or modify example problems to start solving nonlinear programming problems with up to 10 million variables through a web-interface.
Documentation
APMonitor documentation gives details on the modeling language and example applications. Compare with other popular modeling languages.

Discussion Forum and Webinars
Users share experiences and collaborate through an online discussion forum and regularly scheduled webinars.
YouTube Channel
View tutorials, applications, presentations, and join a community of users.

APM Python Interface
Python gives users an open-source option for solving nonlinear programming problems with a growing community of users.
APM MATLAB Interface
MATLAB provides a powerful mathematical scripting language to improve the capability of optimization solutions.

Computational Tools Course
Apply computational tools to solve engineering problems. Includes tutorials in spreadsheet programming, MATLAB, and Python for simulation, optimization, and design.
Process Control Course
Control the dynamic behavior of process systems with fundamental modeling principles and numerical computation.

Optimization Course
Apply computer optimization techniques to constrained engineering design. Includes unconstrained and constrained nonlinear algorithms, genetic algorithms, robust design methods, and dynamic systems.
Software Technical Reference
J.D. Hedengren, R. Asgharzadeh Shishavan, K.M. Powell, T.F. Edgar, Nonlinear Modeling, Estimation and Predictive Control in APMonitor, Computers & Chemical Engineering, 2014.