𝗔𝗜-𝗗𝗿𝗶𝘃𝗲𝗻 𝗗𝗲𝗰𝗶𝘀𝗶𝗼𝗻 𝗠𝗮𝗸𝗶𝗻𝗴 𝘂𝗻𝗱𝗲𝗿 𝗨𝗻𝗰𝗲𝗿𝘁𝗮𝗶𝗻 𝗘𝗻𝘃𝗶𝗿𝗼𝗻𝗺𝗲𝗻𝘁𝘀: 𝗧𝗵𝗲𝗼𝗿𝘆, 𝗠𝗲𝘁𝗵𝗼𝗱𝘀, 𝗮𝗻𝗱 𝗜𝗻𝗱𝘂𝘀𝘁𝗿𝗶𝗮𝗹 𝗔𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀

𝗖𝗔𝗟𝗟 𝗙𝗢𝗥 𝗣𝗔𝗣𝗘𝗥𝗦

𝗔𝗜-𝗗𝗿𝗶𝘃𝗲𝗻 𝗗𝗲𝗰𝗶𝘀𝗶𝗼𝗻 𝗠𝗮𝗸𝗶𝗻𝗴 𝘂𝗻𝗱𝗲𝗿 𝗨𝗻𝗰𝗲𝗿𝘁𝗮𝗶𝗻 𝗘𝗻𝘃𝗶𝗿𝗼𝗻𝗺𝗲𝗻𝘁𝘀: 𝗧𝗵𝗲𝗼𝗿𝘆, 𝗠𝗲𝘁𝗵𝗼𝗱𝘀, 𝗮𝗻𝗱 𝗜𝗻𝗱𝘂𝘀𝘁𝗿𝗶𝗮𝗹 𝗔𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀

𝗝𝗼𝘂𝗿𝗻𝗮𝗹:
International Journal of Production Research

𝗣𝘂𝗯𝗹𝗶𝘀𝗵𝗲𝗿:
Taylor & Francis Group

𝗠𝗮𝗻𝘂𝘀𝗰𝗿𝗶𝗽𝘁 𝗗𝗲𝗮𝗱𝗹𝗶𝗻𝗲:
31 January 2027

𝗔𝗯𝗼𝘂𝘁 𝘁𝗵𝗲 𝗦𝗽𝗲𝗰𝗶𝗮𝗹 𝗜𝘀𝘀𝘂𝗲

Recent advances in artificial intelligence (AI), optimization, and data-driven analytics are fundamentally transforming decision-making processes in complex systems operating under uncertainty. Modern industrial and service systems, including manufacturing, logistics, supply chains, transportation, energy, and healthcare, increasingly operate in dynamic and stochastic environments characterised by demand fluctuations, disruptions, incomplete information, evolving system states, and operational risks.

This Special Issue aims to provide a platform for cutting-edge research on AI-driven decision-making under uncertain environments, with particular emphasis on methodologies and real-world applications that integrate AI techniques with operations research, optimization, simulation, control, and industrial engineering approaches. Both theoretical and applied contributions addressing uncertainty-aware intelligent decision-making across industrial and service systems are welcomed.

The Special Issue is organised in conjunction with APIEMS 2026. Selected high-quality conference papers will be invited to submit extended versions, while the issue remains open to general submissions from researchers worldwide.

𝗧𝗼𝗽𝗶𝗰𝘀 𝗼𝗳 𝗜𝗻𝘁𝗲𝗿𝗲𝘀𝘁

Submissions may address, but are not limited to:

• AI-driven decision-making under uncertainty
• Production planning and scheduling in stochastic and dynamic environments
• Reinforcement learning for uncertain industrial systems
• Stochastic optimization and robust operational strategies
• AI-enabled statistical quality control and process improvement
• Hybrid AI and optimization approaches for uncertain environments
• Data-driven optimization and prescriptive analytics
• AI-enhanced supply chain and logistics management under disruptions
• Real-time and adaptive decision-making systems
• Simulation-based optimization and digital twins under uncertainty
• Agentic AI and autonomous industrial systems
• Explainable and trustworthy AI for operational decision-making
• AI for resilient and sustainable operations
• Industrial applications and case studies of AI-driven decision systems

𝗦𝗽𝗲𝗰𝗶𝗮𝗹 𝗜𝘀𝘀𝘂𝗲 𝗛𝗶𝗴𝗵𝗹𝗶𝗴𝗵𝘁𝘀

• Interdisciplinary studies demonstrating practical relevance and industrial applicability are particularly encouraged
• Research offering managerial insights for complex decision-making problems under uncertainty is highly valued
• Open science practices, including sharing of data, code, models, prompts, and replication materials, are strongly encouraged to promote transparency and reproducibility

𝗦𝘂𝗯𝗺𝗶𝘀𝘀𝗶𝗼𝗻 𝗚𝘂𝗶𝗱𝗲𝗹𝗶𝗻𝗲𝘀

• Submission portal opens on 1 October 2026
• Manuscript submission deadline: 31 January 2027
• All submissions will undergo the journal's standard rigorous peer-review process

𝗔𝗯𝗼𝘂𝘁 𝘁𝗵𝗲 𝗝𝗼𝘂𝗿𝗻𝗮𝗹

The International Journal of Production Research publishes high-quality research on production systems, operations management, industrial engineering, supply chains, manufacturing technologies, and data-driven decision-making. The journal serves as a leading international platform for advancing theoretical and applied research in production and operations systems.

𝗦𝗽𝗲𝗰𝗶𝗮𝗹 𝗜𝘀𝘀𝘂𝗲 𝗘𝗱𝗶𝘁𝗼𝗿𝘀

• Hyun-Jung Kim (Managing Guest Editor), KAIST, South Korea
Email: hyunjungkim@kaist.ac.kr

• Shu-Kai Fan, National Taipei University of Technology, Taiwan
Email: morrisfan@mail.ntut.edu.tw

• Fugee Tsung, Hong Kong University of Science and Technology, Hong Kong
Email: season@ust.hk

• Thomas Volling, Technical University Berlin, Germany
Email: volling@pom.tu-berlin.de

• Jang Ho Kim, Korea University, South Korea
Email: janghokim@korea.ac.kr

• Dong-Young Lim, Ulsan National Institute of Science and Technology, South Korea
Email: dlim@unist.ac.kr

𝗣𝗼𝘀𝘁𝗲𝗱 𝗼𝗻 𝗦𝗲𝗿𝘃𝗶𝗰𝗲𝗦𝗲𝘁𝘂 𝗔𝗰𝗮𝗱𝗲𝗺𝗶𝗰𝘀 — 𝗣𝗿𝗲𝗺𝗶𝗲𝗿 𝗣𝗹𝗮𝘁𝗳𝗼𝗿𝗺 𝗳𝗼𝗿 𝗔𝗰𝗮𝗱𝗲𝗺𝗶𝗰 𝗢𝗽𝗽𝗼𝗿𝘁𝘂𝗻𝗶𝘁𝗶𝗲𝘀 & 𝗥𝗲𝘀𝗲𝗮𝗿𝗰𝗵 𝗖𝗼𝗹𝗹𝗮𝗯𝗼𝗿𝗮𝘁𝗶𝗼𝗻

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