Model-size reduction techniques for large-scale biomass production and supply networks

This paper is concerned with developing several model-size reduction techniques for the analysis of large-scale renewable production and supply networks. They are (i) Reducing the connectivity in a biomass supply chain network, (ii) Eliminating unnecessary variables and constraints, (iii) Merging the collection centres. The proposed model-size reduction techniques brought computational time improvements of several magnitudes compared, with the high performance linear system solution techniques and still with a little loss in accuracy. When the methods are combined the time reductions are more significant. A proposed procedure for combining the methods can be implemented for any supply chain model with a large number of components.

► Model-size reduction techniques has been developed for the analysis of large-scale renewable production and supply networks. ► Technique A is reducing the connectivity in a biomass supply chain network. ► Technique B is eliminating unnecessary variables and constraints. ► Technique C is aggregating the network and the synthesis process by merging the collection centres. ► These techniques brought computational time improvements with a little loss in accuracy.