Accurate Vessel Capacity Models (VCMs) expressing thetrade-off between different container types that can be stowed on containervessels are required in core liner shipping functions such as uptake-,capacity-, and network management. Today, simple models based on volume,weight, and refrigerated container capacity are used for these tasks,which causes overestimations that hamper decision making. Though previouswork on stowage planning optimization in principle provide finegrainedlinear Vessel Stowage Models (VSMs), these are too complexto be used in the mentioned functions. As an alternative, this papercontributes a novel framework based on Fourier-Motzkin Eliminationthat automatically derives VCMs from VSMs by projecting unneededvariables. Our results show that the projected VCMs are reduced byan order of magnitude and can be solved 20–34 times faster than theircorresponding VSMs with only a negligible loss in accuracy. Our frameworkis applicable to LP models in general, but are particularly effectiveon block-angular structured problems such as VSMs. We show similarresults for a multi-commodity flow problem
