Recent extreme economic, social, and environmental changes have made the design of gas- oline supply chain (GSC) networks a major challenge, while sustainability and resilience are emerging as the concerns of communities. This paper presents a novel two-stage sce- nario-based mixed stochastic-possibilistic programming model for designing a three-eche- lon GSC by considering sustainability and resilience criteria simultaneously. The configu- ration of the network and pre-disruption risk mitigation options are determined in the first stage of the model, whereas distribution plans, reconfiguration of the chain, and restoration of the lost capacities are delineated in the second stage. Resilience dimensions, includ- ing design quality, and proactive and reactive capabilities, are considered in the design of the chain, and sustainability criteria are addressed via the cost of network establishment, environmental effects of CO2 emissions, and social effects of the network development on improving job opportunities or economic conditions of local areas. The solution procedure includes scenario planning, handling imprecise parameters, determining scenario-based variables, and finding the Pareto Front. Notably, for the sake of handling high-impact, low- probability disruption scenarios, i.e., disruption scenarios, this research proposes a novel version of the conditional value at risk measure called augmented-CVaR. The validation of the proposed model is examined through a real-world case study in Iran.

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