Using CP Optimizer
Solving constraint programming problems with CP Optimizer
can be broken into three steps: describing the problem, modeling the
problem and finding solutions to the model of the problem. A basic
constraint programming problem model consists of decision variables
and constraints on those variables. Finding a solution to a model
involves constraint propagation and search.
Overview of CP Optimizer
CP Optimizer is a software library which provides constructs for modeling and solving constraint programming problems.
The three-stage method
The three-stage method of constraint programming using CP Optimizer involves describing, modeling and solving.
Describe
The first stage in solving a constraint programming problem with CP Optimizer is to describe the problem using natural language.
Model
The second stage in solving a constraint programming problem with CP Optimizer is to model the problem. The model is composed of decision variables and constraints. The model may also contain an objective.
Solve the problem
The third stage in solving a constraint programming problem with CP Optimizer is to search for a solution and solve the problem.
Scheduling in CP Optimizer
CP Optimizer offers classes and functions specially adapted to modeling and solving problems in scheduling.
Using search parameters
It is possible to set parameters on the CP Optimizer object to control the output, to control the constraint propagation, to limit the search and to control the search engine. It is important to observe that any parameter change from its default is displayed at the head of the search log