Biomass has long been considered one of the most promising feedstock as an alternative primary source to substitute traditional fuels in the transport sectors. However, both biomass intrinsic variability and the fact that several conversion technologies have not reached full maturity make the economic assessment of the production system performance rathefdifficult. This paper proposes a quantitative approach for the strategic design and optimisation of biomass-based supply chains under uncertainty on technology conversion efficiency. The methodology is based on regret theory and allows quantifying both risk and regret with respect to benchmark economic outputs. A Mixed Integer Linear Programming is employed to represent and optimise the profitability of a multi-echelon, multi-period and spatially explicit biomass-based supply chain for bioethanol and bioelectricity production where several conversion technologies are simultaneously taken into account. The modelling framework includes biomass cultivation, transport, conversion, distribution and final usage in alternative fuel vehicles (running either on bioethanol or bioelectricity). Results demonstrate how the methodology can help policy-makers and investors assessing technological options according to their risk aversion attitude. (C) 2017 Elsevier Ltd. All rights reserved.