Playing a critical role in any country, the food industry must guarantee a steady availability of food to consumers. Food supply chains are often vulnerable and unstable, particularly during crises. This vulnerability arises from various challenges and their associated consequences. Currently, stakeholders are being urged to improve supply chain risk management to address multiple disruptive and operational risks. This study proposes an antifragile and agile food Supply Chain Network Design (SCND) that integrates concepts of resiliency, robustness and risk. The model's objective cost function employs combining robust stochastic optimization with Entropic Value at Risk (EVaR). Antifragility is introduced through learning effects on variable parameters and resiliency and agility through flexible capacity and multi-resource and demand satisfaction constraints. The model's performance, including antifragility, is compared against a model without it, showing a cost reduction of 0.42%. The model's application is evaluated using a numerical example, conducting a sensitivity analysis on the antifragility coefficient. Lastly, the research addresses managerial insights and practical implications.