The constraint solver library contains a local search based framework
that allows modeling of a problem using constraint programming primitives (variables, values, constraints).
The search is based on an iterative forward search algorithm.
This algorithm is similar to local search methods; however, in contrast to classical local
search techniques, it operates over feasible, though not necessarily complete,
solutions. In these solutions some variables may be left unassigned. All hard constraints
on assigned variables must be satisfied however. Such solutions are easier
to visualize and more meaningful to human users than complete but infeasible
solutions. Because of the iterative character of the algorithm, the solver can
also easily start, stop, or continue from any feasible solution, either complete
The framework also supports dynamic aspects of the minimal perturbation problem,
allowing the number of changes to the solution (perturbations) to be kept
as small as possible.
The following modules are included in the library:
- Local-search based solver of Constraint Satisfaction and Optimization Problems (ifs-1.3.jar)
- Course Timetabling Extension (cpsolver-1.3.jar)
- Student Sectioning Extension (studentsct-1.3.jar)
- Examination Timetabling Extension (examtt-1.3.jar)