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Use constraint programming techniques to compute solutions for detailed scheduling problems and combinatorial optimization problems
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Solve detailed scheduling problems using CP Optimizer

IBM® ILOG® CP Optimizer is a necessary and important complement to the optimization specialist's toolbox for solving real-world operational planning and scheduling problems. ILOG CP Optimizer contains a robust optimizer that handles the side constraints that are invariably found in such challenges. For pure academic problems such as job-shop, open-shop and flow-shop, it finds solutions that are comparable to solutions found by state-of-the-art specialized algorithms.

Certain combinatorial optimization problems cannot be easily linearized and solved with traditional mathematical programming methods. To handle these problems, ILOG CP Optimizer provides a large set of arithmetic and logical constraints, as well as a robust optimizer that brings all the benefits of a model-and-run development process to combinatorial optimization.

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Learn about black-box expressions in CP Optimizer

## Features

Detailed scheduling problems
• Use modeling features specialized to scheduling like intervals (for activities) and cumul functions (for resources).
• Support business goals by optimizing earliness and tardiness costs, duration costs and non-execution costs.
• Model the work breakdown structure of the schedule and task dependencies as well as multiple production modes.
• Model finite capacity resources and reservoirs.
• Model setup times to compute schedules that define the best possible sizes for batches.

Combinatorial optimization problems
• Use specialized constraints such as all-different, pack, lexicographic, count and distribute for business problems such as facility location, routing and configuration.
• Model with logical constraints as well as a full range of arithmetic expressions, including modulo, integer division, minimum, maximum or an expression, which indexes an array of values by a decision variable.
• Model with discrete decision variables (boolean or integer).
Resources Applications of constraint programming

Explore applications of constraint programming including production problem and scheduling use cases.

ILOG CPLEX Optimization Studio

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Optimization model

Represent business problems mathematically to create effective analytical decision-support applications.

CP Optimizer performance comparison

Learn about CP Optimizer performance comparison for a job shop scheduling problem.

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