The MOSEK Solver uses a state-of-the-art implementation of an Interior Point or Newton-Barrier method, called the Homogeneous Self-Dual method, to solve LP, QP, QCP, and SOCP problems of unlimited size, subject to available time and memory. The XPRESS Solver engine is capable of "crossing over" from the Newton-Barrier method to the Simplex method near the optimal solution, in order to generate sensitivity analysis information. It includes high performance linear algebra methods for the normal equations matrix and advanced ordering algorithms for factorizing this matrix. The XPRESS Solver Engine uses a state-of-the-art implementation of the primal-dual path-following Interior Point or Newton-Barrier method, based on Mehrotra's predictor-corrector algorithm. See the discussion of Optimization Problem Types - Quadratic Constraints and Conic Optimization for more information. The Premium Solver Platform includes an SOCP Barrier Solver that uses an Interior Point method to solve LP, QP, QCP, and SOCP problems up to 2,000 decision variables with excellent performance. It can handle problems of unlimited size, subject to available time and memory. The KNITRO Solver includes an advanced active set method for solving linear and quadratic programming problems, that also exploits sparsity and uses modern matrix factorization methods. The Large-Scale SQP Solver for the Premium Solver Platform uses a state-of-the-art implementation of an active set method for solving linear (and quadratic) programming problems, which fully exploits sparsity in the model to save time and memory, and uses modern matrix factorization methods for numerical stability. Both of these Solver engines can handle an unlimited number of variables and constraints, subject to available time and memory. The XPRESS Solver Engine and Gurobi Solver Engine both use a highly tuned, state-of-the-art implementation of the primal and dual Simplex method, with advanced strategies for matrix updating and refactorization, multiple and partial pricing and pivoting, and overcoming degeneracy. It handles problems of unlimited size, and has been tested on linear programming problems of over a million decision variables. The MOSEK Solver includes a state-of-the-art primal and dual Simplex method that also exploits sparsity and uses advanced strategies for matrix updating and refactorization. This Solver engine is available in three versions, handling up to 8,000, 32,000, or an unlimited number of variables and constraints, subject to available time and memory. It uses advanced strategies for matrix updating and refactorization, multiple and partial pricing and pivoting, and overcoming degeneracy. The Large-Scale LP Solver for the Premium Solver Platform uses a state-of-the-art implementation of the primal and dual Simplex method, which fully exploits sparsity in the LP model to save time and memory. However, this Simplex algorithm does not exploit sparsity in the model. It optionally uses a dual Simplex method to solve LP subproblems in a mixed-integer (MIP) problem. The Premium Solver Platform uses an extended LP/Quadratic version of this Simplex Solver to handle problems of up to 2,000 decision variables. It handles up to 1,000 decision variables. It is limited to 200 decision variables.The Premium Solver uses an improved primal Simplex method with two-sided bounds on the variables. The standard Microsoft Excel Solver uses a basic implementation of the primal Simplex method to solve LP problems.
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