Antifragile, sustainable, and agile supply chain network design by considering resiliency, robustness, risk, and environmental requirements.

This research suggests an Antifragile, Sustainable and Agile Supply Chain Network Design (ASASCND) as a new network design that integrates these concepts considering resiliency, robustness, risk, and environmental requirements. The cost function combines a novel method with robust stochastic optimization and Entropic Value at Risk (EVaR). This model combines expected value, maximum and EVaR of cost as an objective function. This research adds antifragility by the effect of learning on variable parameters, sustainability by considering the environmental and social issues, resiliency and agility by flexible capacity, and multi-resource and demand satisfaction constraints to the model. The case study is in the automotive industry. This model compares the main problem by considering antifragility without thinking about antifragility. The ASASCND cost is - 0.3% less than without considering antifragility. In addition, when the conservatism coefficient grows, the cost function increase. In addition, the antifragility coefficient and the confidence level affect positively, and the agility coefficient negatively affects the cost function. Expanding the model scale changes the cost function and time computation because the antifragility coefficient changes variable cost. Finally, managerial insights and practical implications are explained.