  Five ordering algorithms for the nonserial dynamic programming algorithm for
solving sparse discrete optimization problems are compared in this paper. The
benchmarking reveals that the ordering of the variables has a significant
impact on the run-time of these algorithms. In addition, it is shown that
different orderings are most effective for different classes of problems.
Finally, it is shown that, amongst the algorithms considered here, heuristics
based on maximum cardinality search and minimum fill-in perform best for
solving the discrete optimization problems considered in this paper.
