A circular, resilient and global supply chain for an agri-voltaic biofuel: A solar-integrated optimization under uncertainty

Liquid biofuels are a pivotal bridge in the transition from fossils to renewable transport energy, and Jatropha, which is known as a non-food, drought-tolerant crop, fits arid and semi-arid regions well. This study models the end-to-end supply chain for producing liquid biofuel from Jatropha seed. As Jatropha's siting requirements align with photovoltaic farm suitability, the framework explicitly integrates on-site solar so that a substantial share of extraction-plant electricity is supplied by photo-voltaic, yielding a solar-integrated supply chain. The final biofuel is exported to foreign markets under existing international agreements, reflecting real trade flows and policy constraints. Responding to the need for location-intelligent, uncertainty-aware planning, this study proposes a two-phase “data-to-decision” framework that (i) fuses Monte Carlo disruption simulation, k-means scenario reduction, multi-model demand forecasting, Geographical Information System land screening, and Fuzzy-Best-Worst weighting, then (ii) embeds those inputs in a mixed-integer, two-stage, robust-possibilistic optimization solved via an augmented ε-constraint method. Applied to a five-year Iranian case study, the framework compresses 90 hazard scenarios to just 5 with less than 3% optimality loss, while achieving a tenfold improvement in run-time. Incorporating robust–resilient design increases the share of capital expenditures from 6% to 13% and reduces average profit by about 7%, but it also caps worst-case profit loss at −4% compared to −18% under a deterministic design. At the same time, it lowers life-cycle environmental impacts by more than 20% at only a 6% profit trade-off. The framework offers a transferable, decision-ready blueprint to deliver siting maps, phased investments, and quantified profit–impact trade-offs.