Preparative size-exclusion chromatography suffers from low selectivity and productivity. Empirical optimization of operating conditions constitutes a laborious task due to many parameters. Here, a modeling framework based on linear systems theory is presented for predicting the influence of volume overloading. Impulse-responses characterizing system behavior are derived from experimental data by maximum entropy deconvolution. Theoretical derivations are validated experimentally by study of a model system and chromatography of human influenza virus. By application of the theory it is demonstrated how group separation operations can be optimized with respect to yield, purity, productivity and dilution of the product.