Build and solve complex optimization models to identify the best possible actions
IBM® ILOG® CPLEX® Optimization Studio is a prescriptive analytics solution that enables rapid development and deployment of decision optimization models that use mathematical and constraint programming. With this decision optimization technology, you can:
Translate business problems to optimization models and solve them using proven optimization solvers.
Uncover mathematical programming, constraint programming and constraint-based models that use powerful solvers such as CPLEX Optimizer and CP Optimizer.
Choose from on-premises, cloud and hybrid deployment options to successfully deliver prescriptive analytics through mathematical and constraint programming.
CPLEX is engineered for high-throughput, large-scale optimization across diverse industries. You can Solve LP, MIP, MIQCP and SOCP models using advanced algorithms such as simplex and barrier methods, combined with branch-and-bound, cutting planes and pre-solve techniques.
Solve combinatorial models with discrete variables and tackle scheduling problems using CP Optimizer. Leverage temporal constraints, integer variables, and domain reduction for efficient solutions. Ideal for resource planning, workforce scheduling, manufacturing optimization, packing, assignment and other complex combinatorial challenges across industries.
Model complex optimization problems using OPL (Optimization Programming Language), a declarative language with native support for sets, arrays, tuples and both linear and non-linear constraints. It also supports scheduling-specific constructs such as intervals (activities) and Cumul functions (resources). This simplify the modelling process compared to general-purpose programming languages.
The Integrated Development Environment (IDE) features a constraint-aware editor, project manager and solution visualizer. Debug, profile and run models locally or on IBM Cloud with full control and transparency for OPL-based development. Scripting is supported via JavaScript.