Decision-support systems in container terminal automation: a systematic review of digital twin-expert system integration

Container terminals increasingly deploy digital twins (DTs) for automation and real-time operational visibility, yet most DTs lack embedded decision-making capabilities. This study systematically examines how expert systems (ES) can augment DTs with predictive reasoning and adaptive control through a PRISMA-guided review of 75 peer-reviewed studies. Expert validation via the Fuzzy Delphi Method identifies nine feasible ES configurations, with IoT-based demand response and fuzzy logic systems rated highest. The review uncovers four core DT-ES integration mechanisms, cognitive reasoning, system adaptation, cross-domain coordination, and sustainability optimisation, and assesses twelve technical and organisational implementation challenges. These findings contribute to a structured framework for cognitive terminal architecture that shifts DTs from passive simulators to autonomous decision-makers. Moreover, it supports intelligent maritime operations by aligning ES capabilities with DT functions to improve performance, flexibility, and sustainability.