This CAREER project focuses on making food supply systems, especially those for fresh foods, more reliable. Disruptions in food supply systems lead to food waste, struggling businesses, and higher prices for consumers. This project will create math-based tools to help farmers, processors, distributors, and stores make better decisions, even during uncertain situations. These tools will consider how quickly food spoils, how people in the supply chain behave, and how the system can adapt to problems. The Wisconsin dairy industry will be used as an example because it is important to the state and involves perishable products. Overall, the project aims to improve scientific understanding, strengthen the economy, reduce food waste, and support education by developing courses, training teachers, and creating an interactive board game to help students learn about food systems. This project develops an integrated computational framework for modeling, optimizing, and analyzing resilience in food supply chains, with a particular focus on perishable products. It addresses a fundamental gap in supply chain science: the absence of unified models that simultaneously capture perishability dynamics, uncertainty, and decentralized stakeholder behavior. The first research thrust introduces a graph-based recourse-task-network representation that embeds spoilage dynamics and process constraints across all stages of the supply chain. Building on this foundation, the second thrust advances robust optimization under uncertainty through contextual uncertainty sets, enabling two-stage formulations and solution methods that connect long-term planning decisions with real-time operational adjustments. The third thrust develops multi-agent models and associated solution techniques to represent heterogeneous stakeholder objectives and interactions, supporting the analysis of cooperation, competition, and policy interventions. The Wisconsin dairy supply chain serves as a complex, data-rich tes