IBM ILOG CPLEX Solver The CPLEX solver from IBM ILOG is a high performance solver for (LP), (MIP) and Quadratic Programming (QP/QCP/MIQP/MIQCP) problems. A detailed list of all features supported by CPLEX can be found. CPLEX Linear Programming CPLEX Basic offers various algorithms for solving Linear Programming problems: you can choose between the primal or dual simplex algorithm, the barrier algorithm and the network algorithm. The barrier (or interior point) algorithm offers an approach particularly efficient on large sparse problems. CPLEX can handle sparse matrices very efficiently. A presolver is used to reduce the size of the problem before it is solved, sometimes by an order of magnitude. CPLEX is very robust and reliable. It is capable of solving huge, real-world Optimization problems.

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Almost always the default option settings of CPLEX are sufficient to solve a problem with excellent solution times. CPLEX Mixed Integer Programming CPLEX Intermediate can also solve Mixed Integer Programming problems. The CPLEX branch-and-bound algorithm for solving Mixed Integer Programming problems uses modern features like cutting planes and heuristics to find integer solutions. Combined with the state-of-the-art presolver it makes CPLEX a very powerful tool for solving large and difficult Mixed Integer Programming problems.

Starting from version 12.7, CPLEX features a Benders decomposition algorithm which can be used to solve linear problems with a decomposable structure (including stochastic programming problems with integer variables in the first stage). CPLEX Quadratic Programming CPLEX Basic, Intermediate and Full can also be used to solve Quadratic Programming (QP) problems which are problems with linear constraints and a quadratic objective function. CPLEX Full can also handle the variant with integer variables: Mixed Integer Quadratic Programming (MIQP) problems. Install Adobe Flash Player Linux Mint 16. CPLEX Full can also handle problems that have quadratic constraints: Quadratically Constrained Programming (QCP) problems and Mixed Integer Quadratically Constrained Programming (MIQCP) problems. The QCP and MIQCP solvers support second-order cone constraints, rotated second-order cone constraints, and more general convex quadratic constraints. Parallel CPLEX CPLEX provides a parallel CPLEX option allowing you to take advantage of the availability of additional CPUs to speed up performance while it solves a specific model. CPLEX offers two modes of operation for the functionality of the parallel Mixed Integer Programming optimizer.