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IBM CPLEX

IBM's optimization solver, bundled with CP Optimizer and the OPL modeling language.

IBM ILOG CPLEX Optimization Studio pairs the CPLEX solver (LP, MILP, QP, MIQCP, with simplex, barrier and branch-and-cut) with CP Optimizer, a constraint-programming engine built for scheduling, and the OPL modeling language with its IDE. It integrates with Python (docplex), C++, Java and .NET, and runs as a managed service through Decision Optimization on IBM watsonx.ai or Cloud Pak for Data. It's our choice when a client already runs on IBM tooling, or when a problem mixes combinatorial constraints and linear optimization in the same model.

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[ Why IBM CPLEX ]

What IBM CPLEX brings to your project.

Typical use cases: Shop-floor scheduling, fleet planning, network and portfolio optimization.

01
CPLEX: LP, MILP, QP and MIQCP with simplex, barrier and branch-and-cut.
02
CP Optimizer: constraint programming purpose-built for scheduling and sequencing.
03
OPL and its IDE: readable models, separate data, side-by-side scenarios.
04
Decision Optimization: managed execution on watsonx.ai and Cloud Pak for Data.

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