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  2. Pyomo - Wikipedia

    en.wikipedia.org/wiki/Pyomo

    Pyomo allows users to formulate optimization problems in Python in a manner that is similar to the notation commonly used in mathematical optimization. Pyomo supports an object-oriented style of formulating optimization models, which are defined with a variety of modeling components: sets, scalar and multidimensional parameters, decision variables, objectives, constraints, equations ...

  3. TK Solver - Wikipedia

    en.wikipedia.org/wiki/TK_Solver

    TK Solver's core technologies are a declarative programming language, algebraic equation solver, [1] an iterative equation solver, and a structured, object-based interface, using a command structure. [ 1 ] [ 7 ] The interface comprises nine classes of objects that can be shared between and merged into other TK files:

  4. Gurobi Optimizer - Wikipedia

    en.wikipedia.org/wiki/Gurobi_Optimizer

    Gurobi Optimizer is a prescriptive analytics platform and a decision-making technology developed by Gurobi Optimization, LLC. The Gurobi Optimizer (often referred to as simply, “Gurobi”) is a solver, since it uses mathematical optimization to calculate the answer to a problem.

  5. List of optimization software - Wikipedia

    en.wikipedia.org/wiki/List_of_optimization_software

    Given a transformation between input and output values, described by a mathematical function, optimization deals with generating and selecting the best solution from some set of available alternatives, by systematically choosing input values from within an allowed set, computing the output of the function and recording the best output values found during the process.

  6. Gekko (optimization software) - Wikipedia

    en.wikipedia.org/wiki/Gekko_(optimization_software)

    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.

  7. File:A Byte of Python.pdf - Wikipedia

    en.wikipedia.org/wiki/File:A_Byte_of_Python.pdf

    You are free: to share – to copy, distribute and transmit the work; to remix – to adapt the work; Under the following conditions: attribution – You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses ...

  8. OR-Tools - Wikipedia

    en.wikipedia.org/wiki/OR-Tools

    Google OR-Tools is a free and open-source software suite developed by Google for solving linear programming (LP), mixed integer programming (MIP), constraint programming (CP), vehicle routing (VRP), and related optimization problems. [3] OR-Tools is a set of components written in C++ but provides wrappers for Java, .NET and Python.

  9. Stanford Research Institute Problem Solver - Wikipedia

    en.wikipedia.org/wiki/Stanford_Research...

    The Stanford Research Institute Problem Solver, known by its acronym STRIPS, is an automated planner developed by Richard Fikes and Nils Nilsson in 1971 at SRI International. [1] The same name was later used to refer to the formal language of the inputs to this planner.