Guest Editor(s)
Assoc. Prof. Dr. Erfan Babaee Tirkolaee
Email: erfan.babaee@istinye.edu.tr
Affiliation: Department of Industrial Engineering, Faculty of Engineering and Natural Sciences, Istinye University, Istanbul, Türkiye
Homepage:
Research Interests: operations research, mathematical optimization, artificial intelligence and machine learning, soft computing and fuzzy decision-making, sustainable and resilient supply chains, circular economy, logistics and transportation, data-driven decision analytics
Assoc. Prof. Dr. Alireza Goli
Email: goli.a@eng.ui.ac.ir
Affiliation: Department of Industrial Engineering and Future Studies, Faculty of Engineering, University of Isfahan, Isfahan, Iran
Homepage:
Research Interests: supply chain optimization, metaheuristics, artificial intelligence, robust optimization, Industry 4.0, circular economy, vehicle routing, production planning
Prof. Dr. Gerhard-Wilhelm Weber
Email: gerhard.weber@put.poznan.pl
Affiliation: Faculty of Engineering Management, Poznan University of Technology, Poznan, Poland
Homepage:
Research Interests: operations research, mathematical optimization, data science, machine learning, statistics, decision analytics, systems engineering, sustainable logistics and supply chains
Summary
Agri-food supply chains are increasingly shaped by climate uncertainty, resource scarcity, food loss, volatile demand, and the need for greater traceability and resilience. At the same time, artificial intelligence, machine learning, soft computing, intelligent automation, optimization, digital twins, the Internet of Things, computer vision, and advanced analytics are creating new opportunities to improve decisions from farm production and processing to logistics, distribution, and retail.
This Special Issue focuses on intelligent and computational approaches for sustainable, resilient, and data-driven agri-food supply chains, with emphasis on end-to-end coordination rather than isolated farm-level applications. It seeks original research, methodological advances, review studies, and real-world applications that integrate AI and soft computing with operations research, automation, and decision analytics. Particular attention is given to uncertainty, conflicting sustainability objectives, explainability, human-in-the-loop decision-making, and practical deployment within Agri-Food 4.0 and Agri-Food 5.0.
Suggested themes include:
• AI, machine learning, and generative AI for agri-food decision support,
• fuzzy, evolutionary, and hybrid soft-computing methods,
• mathematical programming, metaheuristics, and AI-assisted optimization,
• intelligent automation, robotics, and autonomous agri-food systems,
• IoT, digital twins, edge intelligence, sensing, and computer vision,
• predictive analytics, forecasting, and smart planning,
• blockchain-enabled traceability, transparency, and food safety,
• resilient, circular, climate-smart, and low-carbon supply chains,
• explainable, trustworthy, and human-centered AI for Agri-Food 5.0.
Keywords
intelligent automation, soft computing, artificial intelligence, machine learning, optimization, digital twins, Internet of Things, Agri-Food 5.0, sustainable supply chains, decision analytics
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