The increasing complexity of modern decision-making demands advanced Operations Research (OR) models that integrate Collaborative Intelligence—the synergy between human expertise, Artificial Intelligence (AI)-driven decision support, and distributed problem-solving frameworks. This paradigm enhances adaptability, efficiency, and resilience in complex operations by leveraging multi-agent coordination, human-AI collaboration, decentralized optimization, and machine learning-enhanced decision-making.
Traditional OR methodologies, despite their strengths in static environments, struggle with the dynamic, interconnected, and uncertain nature of modern decision-making. As Russell Ackoff noted in his 1956 article, "The Aging of a Young Profession," OR was already showing signs of stagnation, becoming overly preoccupied with mathematical techniques rather than addressing real-world problems holistically. By 1979, in "The Future of Operational Research is Past," he further criticized OR for prioritizing optimization within narrow constraints instead of embracing a systemic, interdisciplinary approach. Modern applications like logistics, production, service systems, and emergency response require more adaptive and interactive OR models. Collaborative Intelligence offers a transformative approach, enabling real-time interaction among humans, AI agents, and mathematical models to optimize problem-solving and system performance.
The rapid advancements in AI have revolutionized decision-making across OR domains. However, fully autonomous AI systems face challenges in handling uncertainty, ethical considerations, and interpretability, particularly in high-stakes environments. Collaborative Intelligence bridges this gap by combining the computational power of AI with human intuition, adaptability, and ethical reasoning, fostering trust and robustness in decision-making.
This special issue explores cutting-edge methodologies, theoretical advancements, and practical applications of Collaborative Intelligence in OR. We invite high-quality contributions that address how human expertise and AI can collaboratively enhance decision-making, improve system resilience, and optimize complex operational environments. We welcome original research contributions that propose innovative mathematical models, algorithms, and applications of OR for collaborative decision-making, resilience planning, decentralized optimization, and dynamic problem-solving in complex operational environments. Submissions should demonstrate theoretical rigor and practical relevance, focusing on advancing the state of the art in Collaborative Intelligence.
This special issue aims to provide a platform for researchers and practitioners to share insights, methodologies, and case studies that highlight the transformative potential of Collaborative Intelligence in OR.