Global energy consumption shows a steady upward trend until 2030, with liquid fuels, in particular biodiesel, accounting for a large share of fuel demand for the transport sector. One way to increase its economic and environmental benefits is through optimization of all activities across the supply chain. However, the presence of uncertainties concerning the supply chains parameters may cause to the risk of releasing large amounts of GHG emissions and increasing the total costs and prices of biodiesel on the markets. One way to predict this is by analysing the results obtained by applying mathematical approaches to the design of sustainable supply chains for different scenarios. The study proposes a MILP (mixed integer linear programming) model for optimal design of a sustainable biodiesel/diesel supply chain using different feedstock. It aims to determine the optimal level of the following: arable land and costs for cultivation of feedstock, number, locations, and capacities of biorefineries, transportation network; amounts of feedstock and biodiesel transported between regions while satisfying an economic or an environmental criterion, with the other being set as a constraint. The approach has been implemented on a real case study from Bulgaria. Four optimization problems have been formulated using both criteria for two scenarios - Scenario 1, in which 27 blending centers have been considered and Scenario 2, in which only one blending center has been considered. The obtained results from solving the optimization problems using both criteria for Scenario 1 results in a reduction of the generated GHG emissions with 503 (kg (CO2eq)/d) and 3,136 (kg (CO2eq)/d) at both criteria and the total annual costs with 240,576 ($) at environmental criterion. The analysis of the obtained results shows that the decision made regarding the number of blending centers has an impact on the sustainable operating the biodiesel/diesel supply chain.