  We propose a new global SPACING constraint that is useful in modeling events
that are distributed over time, like learning units scheduled over a study
program or repeated patterns in music compositions. First, we investigate
theoretical properties of the constraint and identify tractable special cases.
We propose efficient DC filtering algorithms for these cases. Then, we
experimentally evaluate performance of the proposed algorithms on a music
composition problem and demonstrate that our filtering algorithms outperform
the state-of-the-art approach for solving this problem.
