IBM ILOG CPLEXEasily embed analytical capabilities within your decision supportapplications

World’s most trusted solver

Highlights

■ High-performance solver with

unmatched speed and reliability

■ Proven in over a thousand

mission-critical deployments

■ Handles business problems

with millions of constraints and

decision variables

■ Fundamental algorithms

include simplex, barrier, and

mixed integer optimizers

■ Multiple programming and

modeling interfaces

Smarter decisions through applied

mathematics

Complex organizations need to plan

their operations more effectively than

ever before. Decision makers must:

● Anticipate best-case, expected-case and

worst-case scenarios● Understand trade-offs, alternatives, bot-

tlenecks and inconsistencies● Develop plans and schedules that can

be adapted in the course of operations

Mathematical programming can help.

IBM® ILOG CPLEX® solves complex

business planning and scheduling

problems that are beyond the capabili-

ties of the human brain or modern

spreadsheets.

Widely deployed in critical business

applications

Whether you need to design an airline

network, a six-month production plan, a

portfolio management strategy or a

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workforce schedule, CPLEX offers a

solution. Nearly all software providers in

supply chain management and major

companies in manufacturing, trans-

portation and logistics, financial serv-

ices, energy and utilities, and many

other industries, rely on CPLEX in their

mission-critical applications. In fact,

more than 1,300 ILOG commercial cus-

tomers, including one-third of the

Global 500 and researchers at more

than 1,000 universities, depend on

CPLEX’s unequaled solving power, sta-

bility and flexibility.

High-performance engine: speed plus

reliability

CPLEX not only tackles large, real-

world problems with astonishing speed,

it does so with unmatched dependabil-

ity and stability. Used in thousands of

deployments worldwide, CPLEX consis-

tently delivers robust, actionable plans

and schedules while ensuring top-line

measures, such as goals for profitability,

revenue and social responsibility, includ-

ing carbon footprint, are met.

Fundamental algorithms

CPLEX comes with the fastest,

most reliable implementations of the

fundamental algorithms for solving

demanding mathematical optimization

problems. CPLEX provides flexible,

high-performance optimizers for solving

linear programming, mixed integer pro-

gramming, quadratic programming,

quadratically constrained programming

(including second-order cone programs)

and mixed integer quadratically con-

strained programming problems.

It can handle problems with millions of

constraints and variables, and consis-

tently sets performance records for

mathematical programming. All CPLEX

algorithms are tightly integrated with

cutting-edge presolve algorithms that

reduce problem sizes and solve times

without requiring any special user inter-

vention. Each optimizer has numerous

options for tuning solving strategies for

specific problems.

CPLEX Simplex Optimizers:

Implements the primal simplex and dual

simplex methods for linear and quad-

ratic programming. CPLEX also pro-

vides an incredibly fast implementation

of the network simplex method, which

is specifically created for network prob-

lems, with or without side constraints.

CPLEX Barrier Optimizer: Provides

an alternative to the simplex method for

solving linear and quadratic problems,

and an approach for solving quadrati-

cally constrained problems. Based on a

primal-dual predictor-corrector method,

the CPLEX Barrier Optimizer provides

unmatched performance for solving

large-scale linear and quadratic prob-

lems. CPLEX Barrier Optimizer includes

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the CPLEX Crossover algorithm, which

converts the solutions created by the

barrier algorithm into basic solutions

that are typically provided by the sim-

plex method and used for fast restarts

and sensitivity analysis.

CPLEX Mixed Integer Optimizers:

Employs a branch-and-bound tech-

nique that takes advantage of innova-

tive cutting-edge strategies to provide

high-performance solutions for the

hardest mixed integer programs.

CPLEX can solve mixed integer linear,

mixed integer quadratic and mixed

integer quadratically constrained prob-

lems. CPLEX Mixed Integer Optimizers

include the CPLEX presolve algorithm,

sophisticated cutting-plane strategies

and feasibility heuristics. CPLEX Mixed

Integer Optimizers provide default and

parameter settings that work well for

most problems but users can cus-

tomize the search strategy or select

specialized techniques. They can cus-

tomize the optimizers’ cutting-plane

and heuristics strategies, and include

their own when problem-specific tech-

niques are valuable. Users can state

whether it is more important to find an

optimal solution or quickly determine a

good feasible solution, and CPLEX

Mixed Integer Optimizers will automati-

cally adjust their solution strategies to

provide the desired behavior. Users can

also direct the optimizers to return mul-

tiple solutions to explore the effects of

subjective preferences on the solution

space.

CPLEX Parallel Optimizers:

Automatically takes advantage of multi-

ple CPUs to solve extremely difficult

problems with CPLEX Parallel Barrier

and CPLEX Parallel MIP Optimizers.

The CPLEX Parallel Barrier Optimizer

achieves significant speedups over its

serial counterpart on a wide variety of

classes of linear programming prob-

lems. The CPLEX Parallel MIP Optimizer

implements a deterministic mode of

operation that produces a repeatable,

invariant solution path, and an

opportunistic mode that takes full

advantage of parallelism for potentially

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better performance. CPLEX Parallel

Optimizers can substantially reduce the

time for solving large linear and difficult

mixed integer programs. In an alterna-

tive use of multiple processors, CPLEX

Concurrent Optimizer uses different

algorithms on different CPUs in a race

to find the best way to solve a problem.

Easily accessible from multiple interfaces

Operations research (OR) practitioners,

engineers, scientists and software

developers can access CPLEX through

their preferred modeling and develop-

ment interfaces. Connectors to popular

tools such as Microsoft® Excel and

MATLAB® are available. CPLEX is also

interoperable with the most popular

optimization modeling tools, with full

compatibility from the IBM® ILOG OPL-

CPLEX Development System, and

access from AIMMS, AMPL, GAMS,

MPL and Microsoft Solver Foundation.

For those embedding CPLEX in their

software applications, component

libraries are provided that are specifi-

cally created for such programming

interfaces as C, C++, .NET, Java™ and

Python®, and other languages are sup-

ported through the C interface.

Additionally, ILOG offers the Interactive

Optimizer, a command-line utility that

lets users read and write problem files

and tune the performance of any

CPLEX algorithm to the requirements of

a specific problem.

CPLEX Component Libraries

CPLEX Component Libraries provide

the features and flexibility that mathe-

matical programming developers need

to create customized applications for

solving both simple and complex

optimization problems. The libraries

include C, C++, .NET, Java and Python

programming interfaces that help devel-

opers use most programming lan-

guages to efficiently embed CPLEX

technology directly into their applica-

tions. The programming interfaces pro-

vide a comprehensive set of routines for

defining, solving, analyzing, querying

and creating reports for mathematical

programming problems and solutions.

For example, routines are provided to

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direct the solution process and com-

pletely control CPLEX messages, and

help developers debug their own

CPLEX applications.

CPLEX provides both a traditional

matrix orientation for representing

mathematical models and a higher-level

representation that uses modeling

objects to help the developer to take

advantage of object-oriented program-

ming approaches. Developers can state

their constraints in the traditional math-

ematical programming form, using lin-

ear or quadratic expressions on these

modeling objects, or alternatively they

can state constraints using logical

expressions to improve readability and

maintainability. Modeling objects are

easily accessible to programmers

using C++, Java, .NET and Python

languages, and help reduce develop-

ment time.

Tools supporting end-to-end development

The IBM ILOG OPL-CPLEX

Development System is the premium

development interface for CPLEX, sup-

porting end user application deploy-

ment from data integration and

optimization model development,

debugging and tuning, through applica-

tion development. Together with the

IBM® ILOG ODM® Enterprise platform,

mathematical programming developers

can rapidly deploy intuitive, interactive

decision-support applications with out-

of-the-box functionality for data analy-

sis, reporting and scenario

management from models built within

OPL’s integrated development environ-

ment (IDE). This development package

provides all the features for developing,

demonstrating and deploying optimiza-

tion applications, with or without IT

support. In addition to CPLEX, the

OPL-CPLEX Development System

includes IBM® ILOG CP Optimizer®, a

second-generation constraint program-

ming engine for automatically solving

detailed scheduling problems and

certain combinatorial optimization prob-

lems that cannot be easily linearized

and solved using traditional mathemati-

cal programming methods—making it

the perfect addition to every OR practi-

tioner’s toolkit.

For more information

For more information about IBM ILOG

CPLEX and the IBM ILOG Optimization

Suite, including customers, contact an

IBM ILOG Sales Representative near

you or visit www.ilog.com/products/

optimization.

© Copyright IBM Corporation 2009

IBM CorporationSoftware GroupRoute 100Somers, NY 10589 U.S.A.

Produced in the United States of AmericaJuly 2009All Rights Reserved

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