The need of accounting for resilience in global supply chains has been growing from practical and academic points of view. However, there is still the need for developing quantitative decision support models on this issue. In the present work, we propose a novel multi-objective mixed possibilistic, two-stage scenario-based stochastic programming model to handle supplier selection and order allocation problem in a global supply chain under operational and disruption risks. The model minimises cost and political risk, while, maximising resilience of the supply portfolio. Various risk mitigation approaches including: contracting with backup suppliers, fortification of suppliers and procurement of emergency inventory, are considered in the model. In addition, the proposed model determines recovery plans. Reservation level driven Tchebycheff procedure is incorporated in the solution procedure to find Pareto-optimal solutions. The validation of the model via computational experiments demonstrates the applicability of the proposed model and solution method in building a resilient supply portfolio under consideration of operational and disruption risks.

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