Previous publications reviewed methods that compute symmetric permutations to reduce the profile of sparse matrices. Based on this experience, this paper, with the support of extensive experiments, evaluates six low-cost heuristics for profile reduction. The heuristics evaluated are Sloan's algorithm and five variants of this method. Among the algorithms appraised, the Hu-Scott and MPG algorithms yielded the highest number of best profile results when applied to symmetric and nonsymmetric sparsity patterns, respectively.