Redesigned advanced programming interface (API) to allow thread-safe applications. Parallel CPLEX Mixed Integer Solver is introduced.
New memory model for easy C++ integration. Significant performance improvements in primal and dual simplex methods, and CPLEX Barrier Optimizer. Significant performance improvements in primal and dual simplex methods, and ILOG CPLEX Mixed Integer Optimizer. MIP performance improvements and support for mixed integer quadratic programs. NET users and support for quadratically constrained programs. Performance improvements in primal and dual simplex methods and the MIP optimizer. Indicator constraints and solution polishing heuristics are introduced and improvements to infeasibility analysis are made. Performance improvements in the primal simplex and barrier methods, as well as the MIP optimizer. The MIP solution pool feature and the performance tuning utility are introduced. Deterministic parallel barrier is also included.īreakthrough performance gains for mixed integer programming (MIP) models and enhanced parallel MIP optimization. Includes connectors for Python, MATLAB and Excel. The first version after IBM acquired ILOG. More parallelism at the root node, deterministic parallel concurrent LP optimization, along with some additional barrier performance improvements and additional tools for diagnosing ill conditioned basis matrices in MIPs.
Support for large nonzero counts that require 64 bit indexing, local optima for non-convex QP, and globalization. MIP performance improvements, random seed parameter to address performance variability, remote object, duals for QCPs, deterministic tuning tool.ĭeterministic time limit support, duals for SOCPs, quadratic expression API in Concert, performance improvements across all algorithms, but especially MIP. Support for nonconvex QPs and MIQPs, distributed parallel MIP and more parallelism at the root node for MIPs. Performance improvements (mainly for SOCP, MISOCP, non-convex QP), support for cloud based optimization.
Generic callback, API recorder to facilitate debugging, subMIP control parameters, Download and Go offering.Īutomated Benders decomposition, modeling assistance tool, runseeds command to better assess performance variability. MIP performance improvements and the addition of a generic branching callback to the other generic callbacks introduced in version 12.8.ĭirect support for multiobjective optimization, callback functionality improvement. MIP performance improvements, new 'emphasis MIP 5' mode, etc. Prior to IBM acquiring ILOG, the CPLEX team published a release history of CPLEX.
The full IBM ILOG CPLEX Optimization Studio consists of the CPLEX Optimizer for mathematical programming, the CP Optimizer for constraint programming, the Optimization Programming Language (OPL), and a tightly integrated IDE. In addition to that AMPL provides an interface to the CPLEX CP Optimizer. The CPLEX Optimizer is accessible through independent modeling systems such as AIMMS, AMPL, GAMS, OptimJ and TOMLAB. Finally, a stand-alone Interactive Optimizer executable is provided for debugging and other purposes. There is a Python language interface based on the C interface. The CPLEX Optimizer has a modeling layer called Concert that provides interfaces to the C++, C#, and Java languages.
The IBM ILOG CPLEX Optimizer solves integer programming problems, very large linear programming problems using either primal or dual variants of the simplex method or the barrier interior point method, convex and non-convex quadratic programming problems, and convex quadratically constrained problems (solved via second-order cone programming, or SOCP).