Learn how optimization and machine learning techniques can be combined for improved business outcomes.

## Solve detailed scheduling problems using CP Optimizer

IBM ILOG® CP Optimizer is a necessary and important complement to the optimization specialists' toolbox for solving real-world operational planning and scheduling problems. CP Optimizer contains a robust optimizer that handles the side constraints that are invariably found in such challenges. For pure academic problems (for example, 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.

## 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)

## Products

#### ILOG CPLEX Optimization Studio

Build and solve complex optimization models to identify the best possible actions that your users should take by using powerful decision optimization algorithms.

#### Decision Optimization for Watson Studio

Build and deploy optimization models in a unified environment and drive business results by combining machine learning and optimization techniques.

#### IBM Decision Optimization Center

Use this platform to build a development platform and GUI, and support data analysis and visualization, scenario management, collaborative planning and what-if analysis.

#### IBM Decision Optimization on Cloud

Use optimization software on the cloud to quickly find optimal solutions for your planning and scheduling, supply chain and asset management challenges.

## Resources

#### Tutorial

Explore key capabilities of ILOG CPLEX Optimization Studio.

#### Product tour: ILOG CPLEX Optimization Studio

Experience the end-to-end journey of solving an optimization problem.

#### Decision Optimization for Watson Studio

Capitalize on the power of prescriptive analytics and build innovative solutions by combining decision optimization and machine learning.

#### Constraint programming technology

Constraint programming technology is used to find solutions to scheduling and combinatorial optimization problems.

#### Optimization model

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

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