Abstract The replacement of fossil fuels with forest biomass should help mitigate Green House Gas (GHG) emissions. However the supply of energy wood is challenging because of high supply costs and rapidly increasing demand. Given, the heterogeneous structure of landownership, contractors and energy producers in Mid-Europe, supply network optimization is of major importance. A multi-criteria optimization problem (MOP) has been formulated, whereby the profit must be maximized and the CO2 emissions have to be minimized. The objective function includes decisions about chipping location, transport mode and volume and terminals used. To solve the MOP, the weighted sum scalarization approach was used to derive Pareto optimal points by stepwise changing weights from maximum profit to minimal CO2 emissions. The MOP was applied to a large-scale network of approximately 10,000 sources, 356 storage locations, 119 freight stations and 228 sinks with a demand of 982,000 t a−1. In an effort to minimize CO2 emissions, 30% of the woody biomass should be delivered chipped from the terminals and more than 50% chipped directly from forest. This results in CO2 emissions of 24.3 kg t−1 and a profit of 3.0 € t−1. The rest has to be transported in solid form directly from forest to plant. By changing the weight to maximize the profit, CO2 emissions will only increase by 4.5%, whereas the profit more than doubles from 3.0 to 7.4 € t−1. The average transport distance increases from 45.7 to 48.1 km and 73% of all terminals are used.