Robust optimal design of sustainable aviation fuel supply chain

One of the pivotal strategies for achieving net-zero aviation emissions is the replacement of conventional jet fuel with Sustainable Aviation Fuels (SAF). The very limited availability of SAF necessitates strategic allocation to flight routes to optimize costs and emission reduction. Addressing this challenge, this paper introduces an innovative adaptive robust optimization framework for the distribution of SAF to flight routes in Canada based on a range of domestic production scenarios, fuel transportation costs, and jurisdictional carbon prices. The objective is to identify the optimal location of potential SAF distribution centers and allocate SAF to flight routes over a 25-year period. This complex problem incorporates flight data from the International Civil Aviation Organization (ICAO) and uncertain projections for SAF production. Leveraging a column and constraint generation algorithm, the paper achieves global optimality in solving the problem. The findings reveal that the proposed robust model results in emission cost savings ranging from 7.13% to 18.19% across various distribution center capacities, consistently outperforming the deterministic model. This underscores the effectiveness of the proposed approach in efficiently distributing available SAF under production uncertainties.