A comparative study of aggregation error bounds for the generalized transportation problem is presented. A priori and a posteriori
error bounds were derived and a computational study was performed to (a) test the correlation between the a priori, the a
posteriori, and the actual error and (b) quantify the difference of the error bounds from the actual error. Based on the results
we conclude that calculating the a priori error bound can be considered as a useful strategy to select the appropriate aggregation
level. The a posteriori error bound provides a good quantitative measure of the actual error.
Keywords Clustering - Network models - Approximation algorithms