Beyond classical optimisation: Toward feasibility-aware computational architectures for synchronised systems

Contemporary logistics, manufacturing, transportation, and cyber-physical systems are increasingly evolving into large-scale synchronised environments in which multiple interdependent resources operate under tightly coupled temporal, structural, and operational constraints. In such settings, the feasibility and correctness of individual decisions are determined not only by local optimisation criteria but also by the ability to preserve synchronisation consistency across distributed processes and dynamically changing system states. As system complexity grows, conventional optimisation approaches often encounter limitations in scalability, computational efficiency, and operational feasibility. Motivated by these challenges, this paper presents a conceptual perspective on the future development of feasibility-aware computational architectures for synchronised multi-resource systems. The proposed vision advocates a multi-layer architectural framework integrating structural feasibility assessment, declarative optimisation models, scalable metaheuristic search mechanisms, and computational reuse strategies. Such an integration aims to support efficient exploration of large decision spaces while preserving synchronisation coherence and operational admissibility. The paper further identifies several open research challenges, including scalability-oriented synchronisation management, feasibility-preserving search processes, systematic exploitation of reusable computational knowledge, and the development of unified benchmarking methodologies for synchronised optimisation environments. Finally, a research agenda is outlined for the design of uncertainty-aware optimisation architectures that provide scalable and robust decision support in increasingly complex and distributed operational systems. The proposed architecture should be understood as a conceptual reference framework and research agenda rather than as a completed and experimentally validated computational system. The STTS example provides an illustrative demonstration of localised feasibility verification and computational reuse, whereas systematic implementation, comparative benchmarking, and scalability validation remain subjects of future research.