<p>This paper proposes a scenario-based fuzzy optimization model for the design of a resilient and circular supply chain network for perishable agricultural products. The model integrates both closed-loop and open-loop logistics flows, enabling the forward distribution of goods and the backward recovery of unsold or expired items. A practical contribution of the developed model is the incorporation of time-dependent returns, where the freshness and timing of product returns determine their routing: early returns are reused at the factory, semi-fresh returns are converted to animal feed, and late returns are processed into compost. In addition, to address real-world practices, the model adopts a possibilistic programming framework that incorporates fuzzy parameters for facility availability under disruption scenarios such as power outages, pest infestations, and refrigeration failures. The proposed model minimizes total system cost while explicitly accounting for resilience and resource recovery through disruption-aware constraints and recovery pathways. The network spans multiple echelons, including farms, a central processing plant, regional distributors, markets, and recovery centers. A real-world case study of a fruit and vegetable supply chain using geospatial data, demand estimates, and expert-informed capacities is conducted to demonstrate the applicability and effectiveness of the proposed model. Results show that protecting only a subset of critical facilities through preventive actions, particularly the central plant and selected distributors, can ensure full network functionality under disruption. Numerical experiments and sensitivity analyses reveal key trade-offs between robustness, circularity, and investment efficiency. The proposed model offers a practical decision-support tool for policymakers and supply chain managers seeking to manage and coordinate risk-aware, time-sensitive, and sustainable agri-food networks.</p>