Decision-support systems for environmental- and social-driven planning and control of agri-food supply chain ecosystems

The agri-food supply chain (AFSC) plays a fundamental role in global food security but also contributes significantly to environmental degradation and socio-economic disparities. Ensuring sustainability in AFSCs requires integrated decision-support systems (DSS) that address environmental and social challenges while improving operational efficiency. However, existing decision-support approaches often fail to incorporate multi-dimensional trade-offs between environmental impact, economic feasibility, and social equity. This dissertation develops a comprehensive, data-driven framework to enhance transparency, sustainability, and social justice within the AFSC. Through decision-support systems, mathematical modeling, optimization techniques, and digital twin technology, this research addresses four key challenges: advancing environmental sustainability, fostering social and economic justice, supporting SC decision-making, and enhancing consumer awareness. By integrating descriptive, prescriptive, and predictive approaches, this thesis bridges gaps in existing research, particularly the lack of consumer-focused sustainability tools and the need for unified models linking social and environmental concerns. A central innovation is a Digital Twin model, which provides real-time insights into the environmental and social impacts of food production, distribution, and consumption. This tool supports policymakers and stakeholders for a top-down improvement while equipping consumers with clear, data-driven insights into product sustainability, promoting a bottom-up shift toward responsible consumption. Findings demonstrate that integrated DSS and DT technologies enable more sustainable food production, optimize logistics, and provide transparency for stakeholders. This research contributes to a holistic, scalable framework for sustainable AFSC planning and control by combining mathematical modeling, optimization techniques, and digital tools. This work provides practical insights for policymakers, industry practitioners, and researchers, supporting the transition toward a more resilient, equitable, and environmentally responsible food system.