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2. Linear programming - Wikipedia

   en.wikipedia.org/wiki/Linear_programming

   Linear programming is a special case of mathematical programming (also known as mathematical optimization). More formally, linear programming is a technique for the optimization of a linear objective function, subject to linear equality and linear inequality constraints. Its feasible region is a convex polytope, which is a set defined as the ...

3. Simplex algorithm - Wikipedia

   en.wikipedia.org/wiki/Simplex_algorithm

   Simplex algorithm. In mathematical optimization, Dantzig 's simplex algorithm (or simplex method) is a popular algorithm for linear programming. [1] The name of the algorithm is derived from the concept of a simplex and was suggested by T. S. Motzkin. [2] Simplices are not actually used in the method, but one interpretation of it is that it ...

4. 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, JavaScript, Fortran, and C#. It has no external dependencies.

5. List of optimization software - Wikipedia

   en.wikipedia.org/wiki/List_of_optimization_software

   MIDACO – a software package for numerical optimization based on evolutionary computing. MINTO – integer programming solver using branch and bound algorithm; freeware for personal use. MOSEK – a large scale optimization software. Solves linear, quadratic, conic and convex nonlinear, continuous and integer optimization.

6. Karmarkar's algorithm - Wikipedia

   en.wikipedia.org/wiki/Karmarkar's_algorithm

   Karmarkar's algorithm is an algorithm introduced by Narendra Karmarkar in 1984 for solving linear programming problems. It was the first reasonably efficient algorithm that solves these problems in polynomial time. The ellipsoid method is also polynomial time but proved to be inefficient in practice. Denoting by the number of variables, m the ...

7. Mathematical optimization - Wikipedia

   en.wikipedia.org/wiki/Mathematical_optimization

   Mathematical optimization. Graph of a surface given by z = f (x, y) = − (x ² + y ²) + 4. The global maximum at (x, y, z) = (0, 0, 4) is indicated by a blue dot. Nelder-Mead minimum search of Simionescu's function. Simplex vertices are ordered by their values, with 1 having the lowest ( best) value. Mathematical optimization (alternatively ...

8. 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 ...

9. Lis (linear algebra library) - Wikipedia

   en.wikipedia.org/wiki/Lis_(linear_algebra_library)

   Lis (Library of Iterative Solvers for linear systems, pronounced [lis]) is a scalable parallel software library to solve discretized linear equations and eigenvalue problems that mainly arise from the numerical solution of partial differential equations using iterative methods.