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CPLEX Solver: Download, Pricing & Documentation

IBM ILOG CPLEX has been a well known and widely used large-scale solver for over three decades. Its efficiency and robustness have been demonstrated through varied applications in thousands of commercial installations worldwide.

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The Strength of CPLEX, Brought to You by AMPL

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About IBM CPLEX

Developer: IBM Corporation

Current version: 22.1.1

IBM CPLEX is a renowned product from IBM, a global technology leader with a rich history dating back to the early 20th century. CPLEX, standing as an acronym for ‘Complex Linear Programming Expert’, is a high-performance mathematical programming solver specializing in linear programming (LP), mixed integer programming (MIP), and quadratic programming (QP). It was developed to address the complex optimization needs in various industries, ranging from logistics and finance to manufacturing and energy. The genesis of CPLEX traces back to the late 1980s when it was initially created by CPLEX Optimization Inc., a company formed to commercialize the dual simplex algorithm. IBM acquired CPLEX in 2009 as part of its purchase of ILOG, the then-owner of CPLEX. This acquisition not only expanded IBM’s portfolio in business analytics but also reinforced CPLEX’s position as a leading tool for optimization problems, known for its robustness, efficiency, and advanced algorithms. Today, CPLEX remains at the forefront of solving large-scale, complex optimization problems, helping businesses and researchers make better decisions and optimize their operations more effectively.

Problem types supported

Linear and quadratic optimization in continuous and integer variables. Support is provided for both convex and nonconvex quadratic objectives, and for convex quadratic constraints.

Special forms detected

Logical implications in the form of “indicator” constraints. Convex quadratic expressions in objectives, and convex quadratic constraints of elliptic and conic types.

Algorithms available

For continuous problems, primal and dual simplex, interior-point (barrier); for integer problems, advanced branch-and-bound with presolve, feasibility heuristics, and cut generators. For continuous problems comprised mostly or entirely of linear network flow constraints, network simplex.

Special features

Shared-memory parallel processing for barrier, branch-and-bound. Concurrent optimization by several methods to determine best choice. Special facilities for parameter tuning and infeasibility diagnosis.

See also:

 ILOG CP for AMPL, covered by the CPLEX for AMPL license, for access to constraint programming and more general CPLEX handling of logical constraints.

Download CPLEX for All Platforms - Windows, Linux, macOS

Experience the power of CPLEX on the AMPL Portal, available for Windows, Linux, and macOS. 
CPLEX can be used with AMPL from various programming languages using our APIs
Python Logo For Python enthusiasts, CPLEX is also accessible as a module with amplpy, blending seamlessly with your Python projects. Explore more about this integration at AMPL Python Integration.

# Install Python API for AMPL

$ python -m pip install amplpy

 

# Install CPLEX

$ python -m amplpy.modules install cplex

AMPL and CPLEX Pricing

Buy CPLEX individually - or combine with AMPL for a full optimization system

INDIVIDUAL

Best for individuals running on one machine

AMPL Pricing

$3,000 /year

CPLEX Pricing

$4,750 /year

SINGLE-PROCESS

Best for small applications running one process at a time

AMPL Pricing

$4,500 /year

CPLEX Pricing

$7,250 /year

MULTI-PROCESS

Best for large teams or applications to run multiple processes simultaneously

AMPL Pricing

$7,000 /year

+$700 /additional CPU

CPLEX Pricing

$14,000 /year

+$1,200 /additional CPU

Try it before you buy it

Get a free, full-featured AMPL license, with all solvers, to experience the performance, support, and flexibility we provide as part of our product offering.

INDIVIDUAL

Best for individuals running on one machine

AMPL Pricing

$6,000 /purchase
+ $1,200 maintenance annually

CPLEX Pricing

$9,500 /purchase
+ $1,900 maintenance annually

SINGLE-PROCESS

Best for small applications running one process at a time

AMPL Pricing

$9,000 /purchase
+ $1,800 maintenance annually

CPLEX Pricing

$14,500 /purchase
+ $2,900 maintenance annually

MULTI-PROCESS

Best for large teams or applications to run multiple processes simultaneously

AMPL Pricing

$14,000 /purchase
+ $2,400 maintenance annually

+1,400 /additional CPU

CPLEX Pricing

$24,000 /purchase
+ $4,800 maintenance annually

+2,400 /additional CPU

Try it before you buy it

Get a free, full-featured AMPL license, with all solvers, to experience the performance, support, and flexibility we provide as part of our product offering.

INDIVIDUAL

SINGLE-PROCESS

MULTI-PROCESS

Dynamic License Validation Available (License server)

Works seamlessly in containerized cloud environments
Static License Validation Available (Machine fingerprinted)
Works in air-gapped high security environments
# of Users
1 (Named user)
Unlimited
Unlimited
# of Processes
Unlimited
1
Unlimited
# of Machines
1 Machine at a time (Dynamic)
1 Fixed machine (Static)
1 Machine at a time (Dynamic)
1 Fixed machine (Static)
Multiple machines (Dynamic – not to exceed total core count)
1 Fixed machine (Static)
# of Variables/Constraints
Unlimited
Unlimited
Unlimited
CPUs or vCPUs
8 (16 threads)

16 (32 threads)

8 (16 threads)
(Additional cores can be purchased)
Looking for something…more?

Contact us for customized licenses tailored for your teams specific needs

CPLEX and AMPL Pricing

Buy CPLEX individually - or combine with AMPL for a full optimization system

INDIVIDUAL

Best for individuals running on one machine

AMPL Pricing

$3,000 /yearly subscription

or

$6,000 /purchase
+ $1,200 maintenance annually

CPLEX Pricing

$4,750 /yearly subscription

or

$9,500 /purchase
+ $1,900 maintenance annually

SINGLE-PROCESS

Best for small applications running one process at a time

AMPL Pricing

$4,500 /yearly subscription

or

$9,000 /purchase
+ $1,800 maintenance annually

CPLEX Pricing

$7,250 /yearly subscription

or

$14,500 /purchase
+ $2,900 maintenance annually

MULTI-PROCESS

Best for large teams or applications to run multiple processes simultaneously

AMPL Pricing

$7,000 /yearly subscription
+ $700 additional CPU

or

$14,000 /purchase
+ $2,800 maintenance annually

+ $1,400 additional CPU

CPLEX Pricing

$7,250 /yearly subscription

or

$14,500 /purchase
+ $2,900 maintenance annually

Optimizing Outcomes with AMPL and CPLEX

CPLEX downloads are available from the My Downloads page of your account at the AMPL Portal, and are included in the bundles that are used for free trials.

AMPL and IBM CPLEX represent a formidable combination in the realm of optimization and analytics. AMPL, known for its powerful and intuitive modeling language, allows users to describe complex optimization problems with remarkable clarity and conciseness. This ease of modeling, coupled with its flexibility and scalability, makes AMPL a preferred choice for researchers and businesses alike. On the other hand, CPLEX stands out for its exceptional solving capabilities, particularly in linear, mixed-integer, and quadratic programming. It is celebrated for its robustness and efficiency, capable of handling large-scale and complex optimization challenges with remarkable speed and accuracy. 

When used together, AMPL’s streamlined model formulation seamlessly integrates with CPLEX’s solving prowess. This synergy enables users to not only model their optimization problems with greater ease and precision but also to solve them more efficiently. The combination of AMPL’s user-friendly modeling environment and CPLEX’s advanced algorithms offers a comprehensive solution, enhancing decision-making processes and operational efficiency in various sectors, from logistics and supply chain management to finance and energy. The AMPL-CPLEX integration, therefore, provides a potent toolkit for tackling some of the most demanding optimization problems faced in the modern world.

Real-World Applications for CPLEX

CPLEX in Logistics and Supply Chain Management

In the realm of logistics and supply chain management, the CPLEX solver has proven to be an invaluable tool. Its ability to handle complex mixed-integer programming problems makes it ideal for optimizing logistical processes such as route planning, inventory management, and warehouse operations. By using CPLEX, companies can determine the most efficient routes for transportation, leading to significant cost savings and reduced delivery times. This is particularly crucial in industries where timing and efficiency are essential, such as e-commerce and perishable goods.

Furthermore, CPLEX aids in effective inventory management by optimizing stock levels to meet demand without overstocking, thereby reducing holding costs. For warehouse operations, CPLEX can optimize the layout and organization to improve the efficiency of storage and retrieval processes. These optimizations contribute to a more agile and responsive supply chain, capable of adapting to changing market demands and reducing overall operational costs. The use of CPLEX in logistics and supply chain management exemplifies how advanced optimization techniques can lead to tangible business benefits in a highly competitive sector.

In logistics and supply chain management, several key roles utilize CPLEX to enhance operational efficiency and decision-making:

Logistics Analysts: These professionals use CPLEX to optimize shipping routes and schedules. They analyze various logistical parameters, such as delivery times, transportation costs, and vehicle capacities, to find the most efficient routing solutions that minimize costs and maximize on-time deliveries.

Supply Chain Managers: They rely on CPLEX for strategic decisions like inventory management and distribution network design. CPLEX helps them balance stock levels across multiple locations, optimize reorder points, and minimize holding costs while ensuring product availability.

Operations Research Analysts: These specialists apply CPLEX in more complex supply chain problems, such as optimizing the layout of warehouses or distribution centers. They use the tool to model and solve problems related to storage efficiency, material handling, and labor utilization in warehouse operations.

Transportation Planners: In companies with large logistics operations, transportation planners use CPLEX to optimize fleet management. This includes determining the optimal mix of vehicle types, maintenance schedules, and allocation of vehicles to different routes or delivery tasks.

CPLEX in Academic and Research Use

CPLEX is not just a tool for industry professionals; it also plays a pivotal role in academia and research. Its robustness and advanced capabilities make it an excellent resource for students and researchers delving into the complexities of mathematical optimization. In academic settings, CPLEX is used to teach optimization techniques, allowing students to apply theoretical concepts to real-world problems. By working with CPLEX, students gain practical experience in formulating and solving different types of optimization problems, from linear and integer programming to more complex quadratic programming challenges.

Talks and slides archive - Students in a lecture hall looking down from behind towards the lecturer

In research, CPLEX is widely used for developing new optimization algorithms and models. Researchers leverage its advanced features to test and validate their hypotheses and models on a wide range of problems. The solver’s ability to handle large and complex datasets is particularly beneficial in research scenarios where the accuracy and efficiency of the solution process are crucial. Additionally, the availability of academic licenses for CPLEX has fostered its adoption in universities and research institutions, making it a cornerstone tool in the field of optimization research. This widespread use in academia not only contributes to the advancement of the field but also ensures a continuous supply of skilled professionals trained in using state-of-the-art optimization tools like CPLEX.

In academic and research environments, CPLEX is predominantly used by:

Academic Researchers and Professors: These individuals use CPLEX for conducting advanced research in the field of optimization. They explore new algorithms, develop novel optimization models, and contribute to the theoretical understanding of optimization problems. Professors also use CPLEX as a teaching tool, providing students with hands-on experience in solving real-world optimization problems.

Students (Undergraduate and Postgraduate): Students in fields like operations research, industrial engineering, and applied mathematics use CPLEX as part of their coursework and research projects. They learn to formulate and solve various optimization problems, gaining practical skills that are highly valued in industry roles.

Ph.D. Candidates and Postdoctoral Researchers: These researchers use CPLEX for complex, innovative research projects. They often push the boundaries of what’s possible in optimization, tackling large-scale and highly complex problems that contribute to scientific advancements in the field.

Data Scientists in Academic Settings: In some research projects, especially those intersecting with data analytics and machine learning, data scientists use CPLEX to optimize models and algorithms based on large datasets. Their work often involves exploring the synergy between predictive analytics and optimization.

Frequently Asked Questions

CPLEX excels in solving large-scale optimization problems across various domains, including logistics, supply chain management, finance, manufacturing, and energy. It’s particularly effective for problems involving complex decision-making processes and large datasets.

While CPLEX is primarily designed for linear and quadratic problems, it can handle certain types of nonlinearities in mixed-integer programming problems. However, it might not be as efficient for general nonlinear programming as specialized nonlinear solvers.

CPLEX is often compared with other leading optimization solvers like Gurobi and Mosek for its efficiency and speed, particularly in solving large-scale linear and mixed-integer programming problems. The choice between these solvers can depend on specific problem types, licensing costs, and user preferences.

CPLEX offers APIs for several programming languages, including Python, Java, C++, and .NET. This flexibility allows users to integrate CPLEX into a wide range of applications and software environments.

Yes, CPLEX can be integrated with various data analysis and machine learning tools. Its compatibility with popular programming languages and data science platforms enables seamless integration in complex data-driven optimization projects.

Key features of CPLEX include advanced presolving techniques, parallel processing capabilities, robust branch-and-cut algorithms for MIP, and specialized heuristics for quickly finding feasible solutions. These features collectively enhance its efficiency and solution quality.

CPLEX supports business decision-making by providing optimized solutions to complex problems. It helps companies reduce costs, improve operational efficiency, and make strategic decisions based on accurate, data-driven insights. Whether it’s optimizing supply chains, managing financial risks, or planning production, CPLEX provides a solid foundation for informed decision-making.

Further Information & Resources

Instructions for joining the IBM Academic Initiative

CPLEX for AMPL 12.2: CPLEX-for-AMPL-12.2-Users-Guide

IBM CPLEX Solver

IBM ILOG CPLEX has been a well known and widely used large-scale solver for over three decades. Its efficiency and robustness have been demonstrated through varied applications in thousands of commercial installations worldwide.

Getting started with CPLEX

IBM Academic Initiative

CPLEX downloads are available from the My Downloads page of your account at the AMPL Portal, and are included in the bundles that are used for free trials.

Summary

Developer: IBM Corporation

Company website: IBM ILOG CPLEX

Current version: 22.1.1

Problem types supported: Linear and quadratic optimization in continuous and integer variables. Support is provided for both convex and nonconvex quadratic objectives, and for convex quadratic constraints.

Special forms detected: Logical implications in the form of “indicator” constraints. Convex quadratic expressions in objectives, and convex quadratic constraints of elliptic and conic types.

Algorithms available: For continuous problems, primal and dual simplex, interior-point (barrier); for integer problems, advanced branch-and-bound with presolve, feasibility heuristics, and cut generators. For continuous problems comprised mostly or entirely of linear network flow constraints, network simplex.

Special features: Shared-memory parallel processing for barrier, branch-and-bound. Concurrent optimization by several methods to determine best choice. Special facilities for parameter tuning and infeasibility diagnosis.

See also: ILOG CP for AMPL, covered by the CPLEX for AMPL license, for access to constraint programming and more general CPLEX handling of logical constraints.

Further Information

Instructions for joining the IBM Academic Initiative

CPLEX for AMPL 12.2: CPLEX-for-AMPL-12.2-Users-Guide