Solution, Visualization, and Solvers in one package

Increase ease and efficiency with one package for all your needs

pip install gekko

Use pip in the python terminal to easily install

Over 11,000 Monthly Downloads

GEKKO is an object-oriented Python library that facilitates model construction, analysis tools, and visualization of simulation and optimization in a single package.

As a differential and algebraic modeling language, it facilitates the use of advanced modeling and solvers. Gekko simplifies the process by allowing the model to be written in a simple, intuitive format. It accepts a model consisting of constraints and an objective to optimize.

Gekko offers capabilities in machine learning, digital twin simulation, combined empirical/first principles, and model predictive control in an easy to use and understandable Python user interface.

Key Advantages

Gekko provides versatility with objects designed to model, estimate, optimize and control in an easily readable Python environment.

Constrained Predictive Deep Learning

Current development includes physics-based activation functions in predictive deep learning to take advantage of a priori knowledge such as mass or energy balances and improve the magnitude of problems which can be solved and the time it takes to solve them.

Free for Academic and Commercial Use (MIT License)

Hundreds of Industrial Applications

Adjust valves, pumps and other actuators in simulations or with physical systems.

Compiled bytecode backend for efficient solutions

Automatic Differentiation for Exact First and Second Derivatives

Converts differential equations to algebraic form with orthogonal collocation on finite elements.

Interior Point (IPOPT, BPOPT) and Active Set SQP (APOPT) Solvers

Sequential and Simultaneous Solution Modes.

Continuous and Mixed Integer Solutions.

Solving Methods

  • Linear programming (LP)
  • Quadratic programming (QP)
  • Quadratically constrained quadratic program (QPQC)
  • Nonlinear programming (NLP)
  • Mixed integer linear programming (MILP)
  • Mixed integer nonlinear programming (MINLP)

Solving Modes

  • Machine Learning
  • Data reconciliation
  • Real-time optimization
  • Digital twin dynamic simulation
  • Moving horizon estimation
  • Model predictive control

Industries Applied

  • Cogeneration
  • Drilling automation
  • Severe slugging control
  • Solar thermal energy production
  • Solid oxide fuel cells
  • Flow assurance
  • Enhanced oil recovery
  • Essential oil extraction
  • Unmanned aerial vehicles
  • Food and beverage
  • Pulp and paper
  • Polyethylene reactors
  • Polypropylene reactors
  • Butyl rubber production
  • Polyalphaolefins
  • Systems biology