Project Management
Constraint Programming : PROC CLP
The CLP procedure is a finite domain constraint programming solver for constraint satisfaction problems (CSPs) with linear, logical, global, and scheduling constraints. In addition to having an expressive syntax for representing CSPs, the solver features powerful built-in consistency routines and constraint propagation algorithms, a choice of nondeterministic search strategies, and controls for guiding the search mechanism that enable you to solve a diverse array of combinatorial problems.
The Constraint Satisfaction Problem
A CSP is defined by a finite set of variables taking values from finite domains and a finite set of constraints restricting the values the variables can simultaneously take.
A CSP can be defined as a triple 
where
-
is a finite set of
variables.
-
is a finite set of
domains, where 
is a finite set of possible
values that the variable 
can take.
-
is a finite set of constraints
restricting the values that the variables can simultaneously take.
Input Data
Input information is contained in the following data sets:
-
The Activity data set enables you to define an activity, its domain, and any temporal constraints. You
can use this data set in lieu of, or in combination with, an ACTIVITY statement to define activities and constraints
relating to the activities.
- The Constraint data set defines linear constraints, variable types, and bounds on variable domains. It can be used used in lieu of, or in combination with, a LINCON and/or a VAR statement.
Output Data
The output of the CLP procedure is captured in the following data sets:
-
The Solution data set for a standard (nonscheduling) type CSP contains all the solutions that have been
determined by the CLP procedure.
- The Schedule data set for a scheduling type CSP contains all the schedules determined by the CLP procedure.
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