IBM ILOG CPLEX Optimization Studio (often informally referred to simply as CPLEX) is an optimization software package.
History
The CPLEX Optimizer was named after the simplex method implemented in the C programming language. However, today it also supports other types of mathematical optimization and offers interfaces other than C. It was originally developed by Robert E. Bixby and sold commercially in 1988 by CPLEX Optimization Inc. This was acquired by ILOG in 1997 and ILOG was subsequently acquired by IBM in January 2009.[2] CPLEX continues to be actively developed by IBM.
The CPLEX Optimizer has a modeling layer called Concert that provides interfaces to the C++, C#, and Java languages. There is a Python language interface based on the C interface. Finally, a stand-alone Interactive Optimizer executable is provided for debugging and other purposes.
The CPLEX Optimizer is accessible through independent modeling systems such as AIMMS, AMPL, GAMS, OptimJ and TOMLAB. In addition to that AMPL provides an interface to the CPLEX CP Optimizer.
The full IBM ILOG CPLEX Optimization Studio consists of the CPLEX Optimizer for mathematical programming, the CP Optimizer for constraint programming,[4] the Optimization Programming Language (OPL), and a tightly integrated IDE.
Release history
Prior to IBM acquiring ILOG, the CPLEX team published a release history of CPLEX.[5]
Version
Release Date
Key Features
22.1.1
December, 2022
Python 3.7 support dropped, new solver parameter added.[6]
22.1.0
March, 2022
Python 3.9 and 3.10 support added, new solver parameters added.[7]
20.1
December, 2020
MIP performance improvements, new 'emphasis MIP 5' mode, etc.[8]
12.10
December, 2019
MIP performance improvements and the addition of a generic branching callback to the other generic callbacks introduced in version 12.8.
12.9
March, 2019
Direct support for multiobjective optimization, callback functionality improvement.
12.8
December, 2017
Generic callback, API recorder to facilitate debugging, subMIP control parameters, Download and Go offering.
Performance improvements (mainly for SOCP, MISOCP, non-convex QP), support for cloud based optimization.
12.6
December, 2013
Support for nonconvex QPs and MIQPs, distributed parallel MIP and more parallelism at the root node for MIPs..
12.5
October, 2012
MIP performance improvements, random seed parameter to address performance variability, remote object, duals for QCPs, deterministic tuning tool.
12.4
November, 2011
Deterministic time limit support, duals for SOCPs, quadratic expression API in Concert, performance improvements across all algorithms, but especially MIP.
12.3
June, 2011
Support for large nonzero counts that require 64 bit indexing, local optima for non-convex QP, and globalization.
12.2
June, 2010
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.
12.0
April, 2009
The first version after IBM acquired ILOG. Includes connectors for Python, MATLAB and Excel. Deterministic parallel barrier is also included.
11.0
October, 2007
Breakthrough performance gains for mixed integer programming (MIP) models and enhanced parallel MIP optimization. The MIP solution pool feature and the performance tuning utility are introduced.
10.0
January, 2006
Performance improvements in the primal simplex and barrier methods, as well as the MIP optimizer. Indicator constraints and solution polishing heuristics are introduced and improvements to infeasibility analysis are made.
9.0
December, 2003
Performance improvements in primal and dual simplex methods and the MIP optimizer. It includes ILOG Concert Technology for .NET users and support for quadratically constrained programs.
8.0
July, 2002
MIP performance improvements and support for mixed integer quadratic programs.
7.5
December, 2001
ILOG Concert Technology for Java users.
7.0
October, 2000
ILOG Concert Technology for C++ users.
6.5
March, 1999
Significant performance improvements in primal and dual simplex methods, and ILOG CPLEX Mixed Integer Optimizer.
6.0
April, 1998
Significant performance improvements in primal and dual simplex methods, and CPLEX Barrier Optimizer.
5.0
September, 1997
New memory model for easy C++ integration.
4.0.5
March, 1996
Parallel CPLEX Mixed Integer Solver is introduced.
4.0
December, 1995
Redesigned advanced programming interface (API) to allow thread-safe applications.
3.0.8
March, 1995
Parallel CPLEX Barrier Solver is introduced.
3.0
April, 1994
CPLEX Barrier Solver is introduced.
2.1
March, 1993
Introduction of CPLEX Presolve algorithms.
2.0
April, 1992
Performance improvements.
1.2
1991
Support for the dual simplex method and CPLEX Mixed Integer Optimizer.
^Mittelmann, H. D. (10 July 2007), "Recent Benchmarks of Optimization Software", 22nd European Conference on Operational Research, EURO XXII Prague, Czech Republic: Dept of Math and Stats Arizona State University
^Laborie P, Rogerie J, Shaw P, Vilim P (2018). "IBM ILOG CP optimizer for scheduling". Constraints. 23 (2): 210–250. doi:10.1007/s10601-018-9281-x.
^"CPLEX History". CPLEX History as published by ILOG. Archived from the original on 13 April 2009. Retrieved 24 June 2020.
