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Our team has 20+ years of experience in designingĬombinatorial optimization tools for real-life industrial Historically developed since 2007 by ILOG, now IBMĭescendant of ILOG Solver/Scheduler (1992-2007) IBM, IBM / 244 ICAPS 2017 Tutorial © 2017 IBM Corporation Introduction to CP Optimizer for Scheduling No prior knowledge of Constraint Programming is required.Ī (Not So Short) Introduction to CP Optimizer for Scheduling This tutorial, heavily illustrated with examples, gives an overview of CP Optimizer for scheduling. These tools accelerate the development and maintenance of models for complex industrial scheduling problems that will be efficiently solved by the automatic search. The convergence with MP goes even further, with a convergence of the tools and functionalities around the engine like an input/output format, modeling assistance with warnings and conflict refiner, interactive executable, etc. The automatic search provides good out of the box performance and is continuously improving from version to version. In particular CP Optimizer implements a model & run paradigm that does not require the user to understand Constraint Programming or scheduling algorithms: declarative modeling is the only thing that matters. From the very beginning, CP Optimizer was designed with the goal to provide a similar experience as Mathematical Programming (MP) tools like CPLEX, with a strong focus on usability. It provides an algebraic language with simple mathematical concepts such as intervals or functions to capture the temporal dimension of scheduling problems in a combinatorial optimization framework.
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CP Optimizer is a generic Constraint Programming (CP) based system to model and solve scheduling problems (among other combinatorial problems).