Transform your business decision-making with data science
IBM® ILOG® CPLEX® Optimization Studio uses decision optimization technology to optimize your business decisions, develop and deploy optimization models quickly, and create real-world applications that can significantly improve business outcomes.
How? IBM ILOG CPLEX Optimization Studio is a prescriptive analytics solution that enables rapid development and deployment of decision optimization models using mathematical and constraint programming. It combines a fully featured integrated development environment that supports Optimization Programming Language (OPL) and the high-performance CPLEX and CP Optimizer solvers. It’s data science for your decisions.
IBM Decision Optimization is also available within Cloud Pak for Data where you can combine optimization and machine learning within a unified environment— IBM Watson® Studio — that enables AI-infused optimization modeling capabilities.
Translate business problems to optimization models and solve them using powerful CPLEX engines.
Solve a range of optimization problems
Uncover mathematical programming, constraint programming and constraint-based models using CPLEX engines.
Choose your deployment
Choose from on-premises, cloud and hybrid deployment options to successfully deliver prescriptive analytics through mathematical and constraint programming.
Gain better outcomes for many industries
Help reduce operating costs through better allocation of important informaiton with IBM ILOG CPLEX Optimization Studio.
Why IBM ILOG CPLEX Optimization Studio is the best choice for decision-making
Offers established optimization technology with more than 25 years experience
Choose a provider with decades of expertise in optimization technology. The prestigious Edelman Prize is given each year to the best practitioner project in operations research. IBM CPLEX Optimizer is used four times more than any other optimization technology to build innovative solutions for solving difficult challenges by Edelman finalists.
Provides a comprehensive end-to-end solution for solving complex problems
Read how IBM ILOG CPLEX Optimization Studio provides a comprehensive end-to-end solution for even the most complex challenges. This includes integrating with IBM SPSS® Modeler, running optimization algorithms on cloud and allowing for user collaboration and powerful visualizations in an intuitive user interface.
Enables development and deployment of optimization models quickly and accurately
Use OPL, an algebraic modeling language that makes it easier to understand and see constraints, goals and costs. Choose from a large set of interfaces, programming languages or deployment scenarios. Deploy in Java, Python, .NET, C and C++ or with a client/server architecture. Use built-in development tools for debugging, profiling, tuning and conflict detection. Enjoy total flexibility for modeling with a compact and expressive OPL, and an IDE with diverse model development services that no other organization provides.
Read this infographic to see how leading organizations from various industries across the world use IBM ILOG CPLEX Optimization Studio to achieve better outcomes. For example, a global logistics provider creates its next-generation logistics management platform. An arc welding systems and power source manufacturer in Italy reduces inventory by 15 percent and cuts lost orders by 70 percent. A financial services company helps banks reduce cross-shipping fees by 63 percent.
CPLEX Optimization Studio is very agile and provides answers for any scenario. It prepares us for the future by helping us make better decisions.
ÇimSA Çimento Sanayi ve Ticaret A.Ş.
Technically, CPLEX is very easy to deploy and to implement into the techniques we were developing in our framework. So that was key in our decision.
Birome Holo Ba, PhD
Cofounder and CSO
You can’t just write regular programming code for it. You’ve got to model each of these things in an equation, and you’ve got to get that equation balanced and optimized. What CPLEX does is it actually solves this thing.