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  2. 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.

  3. Fifth-generation programming language - Wikipedia

    en.wikipedia.org/wiki/Fifth-generation...

    A fifth-generation programming language (5GL) is a high-level programming language based on problem-solving using constraints given to the program, rather than using an algorithm written by a programmer. [1] Most constraint-based and logic programming languages and some other declarative languages are fifth-generation languages.

  4. List of unsolved problems in computer science - Wikipedia

    en.wikipedia.org/wiki/List_of_unsolved_problems...

    The problem to determine all positive integers such that the concatenation of and in base uses at most distinct characters for and fixed [citation needed] and many other problems in the coding theory are also the unsolved problems in mathematics.

  5. HiGHS optimization solver - Wikipedia

    en.wikipedia.org/wiki/HiGHS_optimization_solver

    HiGHS is open-source software to solve linear programming (LP), mixed-integer programming (MIP), and convex quadratic programming (QP) models. [1] Written in C++ and published under an MIT license, HiGHS provides programming interfaces to C, Python, Julia, Rust, R, JavaScript, Fortran, and C#. It has no external dependencies. A convenient thin ...

  6. Computational problem - Wikipedia

    en.wikipedia.org/wiki/Computational_problem

    Computational problems of this type are called promise problems. The following is an example of a (decision) promise problem: "Given a graph G , determine if every independent set in G has size at most 5, or G has an independent set of size at least 10."

  7. Constraint satisfaction - Wikipedia

    en.wikipedia.org/wiki/Constraint_satisfaction

    Such problems are usually solved via search, in particular a form of backtracking or local search. Constraint propagation is another family of methods used on such problems; most of them are incomplete in general, that is, they may solve the problem or prove it unsatisfiable, but not always. Constraint propagation methods are also used in ...

  8. Dynamic programming - Wikipedia

    en.wikipedia.org/wiki/Dynamic_programming

    If sub-problems can be nested recursively inside larger problems, so that dynamic programming methods are applicable, then there is a relation between the value of the larger problem and the values of the sub-problems. [1] In the optimization literature this relationship is called the Bellman equation.

  9. Interior-point method - Wikipedia

    en.wikipedia.org/wiki/Interior-point_method

    An interior point method was discovered by Soviet mathematician I. I. Dikin in 1967. [1] The method was reinvented in the U.S. in the mid-1980s. In 1984, Narendra Karmarkar developed a method for linear programming called Karmarkar's algorithm, [2] which runs in provably polynomial time (() operations on L-bit numbers, where n is the number of variables and constants), and is also very ...