Gekko (optimization software) (original) (raw)
The GEKKO Python package solves large-scale mixed-integer and differential algebraic equations with nonlinear programming solvers (IPOPT, APOPT, BPOPT, SNOPT, MINOS). Modes of operation include machine learning, data reconciliation, real-time optimization, dynamic simulation, and nonlinear model predictive control. In addition, the package solves Linear programming (LP), Quadratic programming (QP), Quadratically constrained quadratic program (QCQP), Nonlinear programming (NLP), Mixed integer programming (MIP), and Mixed integer linear programming (MILP). GEKKO is available in Python and installed with pip from PyPI of the Python Software Foundation.
| Property | Value |
|---|---|
| dbo:abstract | The GEKKO Python package solves large-scale mixed-integer and differential algebraic equations with nonlinear programming solvers (IPOPT, APOPT, BPOPT, SNOPT, MINOS). Modes of operation include machine learning, data reconciliation, real-time optimization, dynamic simulation, and nonlinear model predictive control. In addition, the package solves Linear programming (LP), Quadratic programming (QP), Quadratically constrained quadratic program (QCQP), Nonlinear programming (NLP), Mixed integer programming (MIP), and Mixed integer linear programming (MILP). GEKKO is available in Python and installed with pip from PyPI of the Python Software Foundation. pip install gekko GEKKO works on all platforms and with Python 2.7 and 3+. By default, the problem is sent to a public server where the solution is computed and returned to Python. There are Windows, MacOS, Linux, and ARM (Raspberry Pi) processor options to solve without an Internet connection. GEKKO is an extension of the APMonitor Optimization Suite but has integrated the modeling and solution visualization directly within Python. A mathematical model is expressed in terms of variables and equations such as the Hock & Schittkowski Benchmark Problem #71 used to test the performance of nonlinear programming solvers. This particular optimization problem has an objective function and subject to the inequality constraint and equality constraint . The four variables must be between a lower bound of 1 and an upper bound of 5. The initial guess values are . This optimization problem is solved with GEKKO as shown below. from gekko import GEKKOm = GEKKO # Initialize gekko# Initialize variablesx1 = m.Var(value=1, lb=1, ub=5)x2 = m.Var(value=5, lb=1, ub=5)x3 = m.Var(value=5, lb=1, ub=5)x4 = m.Var(value=1, lb=1, ub=5)# Equationsm.Equation(x1 * x2 * x3 * x4 >= 25)m.Equation(x1 ** 2 + x2 ** 2 + x3 ** 2 + x4 ** 2 == 40)m.Obj(x1 * x4 * (x1 + x2 + x3) + x3) # Objectivem.solve(disp=False) # Solveprint("x1: " + str(x1.value))print("x2: " + str(x2.value))print("x3: " + str(x3.value))print("x4: " + str(x4.value))print("Objective: " + str(m.options.objfcnval)) (en) |
| dbo:developer | dbr:John_Hedengren |
| dbo:genre | dbr:List_of_numerical_analysis_software |
| dbo:latestReleaseDate | 2021-12-02 (xsd:date) |
| dbo:latestReleaseVersion | 1.0.2 |
| dbo:license | dbr:MIT_license |
| dbo:thumbnail | wiki-commons:Special:FilePath/gekko_logo.png?width=300 |
| dbo:wikiPageExternalLink | https://apmonitor.com/wiki/index.php/Main/GekkoPythonOptimization https://gekko.readthedocs.io/en/latest/ https://machinelearning.byu.edu/ https://github.com/BYU-PRISM/GEKKO https://github.com/BYU-PRISM/GEKKO%7CCross-Platform https://www.nsf.gov/awardsearch/showAward%3FAWD_ID=1547110 https://pypi.org/project/gekko http://apmonitor.com/wiki/index.php/Main/APMonitorReferences |
| dbo:wikiPageID | 57256998 (xsd:integer) |
| dbo:wikiPageLength | 16975 (xsd:nonNegativeInteger) |
| dbo:wikiPageRevisionID | 1092445921 (xsd:integer) |
| dbo:wikiPageWikiLink | dbr:Python_(programming_language) dbr:Enhanced_oil_recovery dbr:MINOS_(optimization_software) dbr:Deep_learning dbr:Mathematical_optimization dbr:SNOPT dbr:Essential_oil dbr:Quadratically_constrained_quadratic_program dbr:List_of_numerical_analysis_software dbr:Mixed_integer_programming dbr:MIT_license dbr:Machine_learning dbr:Backpropagation dbr:Karush–Kuhn–Tucker_conditions dbr:Linear_programming dbr:APMonitor dbr:APOPT dbr:Quadratic_programming dbr:Artificial_neural_network dbc:Mathematical_optimization_software dbc:Numerical_programming_languages dbr:Cogeneration dbr:Oil_well dbr:Solid_oxide_fuel_cell dbr:IPOPT dbr:Optimal_control dbr:Model_predictive_control dbr:Unmanned_aerial_vehicle dbr:Nonlinear_programming dbr:Mixed_integer_linear_programming dbr:John_Hedengren dbr:File:Artificial_Neural_Network_Example.png dbr:File:Optimal_Control_Luus.png |
| dbp:developer | Logan Beal and John Hedengren (en) |
| dbp:genre | dbr:List_of_numerical_analysis_software |
| dbp:latestReleaseDate | 2021-12-02 (xsd:date) |
| dbp:latestReleaseVersion | 1 (xsd:integer) |
| dbp:license | dbr:MIT_license |
| dbp:logo | gekko_logo.png (en) |
| dbp:logoSize | 300 (xsd:integer) |
| dbp:name | GEKKO (en) |
| dbp:operatingSystem | https://github.com/BYU-PRISM/GEKKO%7CCross-Platform |
| dbp:wikiPageUsesTemplate | dbt:Infobox_Software dbt:Reflist dbt:Start_date_and_age dbt:URL dbt:Mathematical_optimization_software |
| dcterms:subject | dbc:Mathematical_optimization_software dbc:Numerical_programming_languages |
| rdf:type | owl:Thing dbo:Software schema:CreativeWork dbo:Work wikidata:Q386724 wikidata:Q7397 |
| rdfs:comment | The GEKKO Python package solves large-scale mixed-integer and differential algebraic equations with nonlinear programming solvers (IPOPT, APOPT, BPOPT, SNOPT, MINOS). Modes of operation include machine learning, data reconciliation, real-time optimization, dynamic simulation, and nonlinear model predictive control. In addition, the package solves Linear programming (LP), Quadratic programming (QP), Quadratically constrained quadratic program (QCQP), Nonlinear programming (NLP), Mixed integer programming (MIP), and Mixed integer linear programming (MILP). GEKKO is available in Python and installed with pip from PyPI of the Python Software Foundation. (en) |
| rdfs:label | Gekko (optimization software) (en) |
| owl:sameAs | wikidata:Gekko (optimization software) https://global.dbpedia.org/id/6pbSv |
| prov:wasDerivedFrom | wikipedia-en:Gekko_(optimization_software)?oldid=1092445921&ns=0 |
| foaf:depiction | wiki-commons:Special:FilePath/Artificial_Neural_Network_Example.png wiki-commons:Special:FilePath/gekko_logo.png wiki-commons:Special:FilePath/Optimal_Control_Luus.png |
| foaf:isPrimaryTopicOf | wikipedia-en:Gekko_(optimization_software) |
| foaf:name | GEKKO (en) |
| is dbo:wikiPageDisambiguates of | dbr:Gekko_(disambiguation) |
| is dbo:wikiPageWikiLink of | dbr:List_of_computer_simulation_software dbr:Algebraic_modeling_language dbr:List_of_optimization_software dbr:Comparison_of_optimization_software dbr:Linear_programming dbr:APMonitor dbr:APOPT dbr:Gekko_(disambiguation) dbr:Modeling_language dbr:Knapsack_problem |
| is foaf:primaryTopic of | wikipedia-en:Gekko_(optimization_software) |
