Autonomous bioinspired algorithms for optimization and distributed decision-making in intelligent infrastructures

Abstract

Intelligent infrastructures require control strategies that overcome the limitations of centralized management. This study critically reviews the 2015–2025 literature on the convergence between bioinspired algorithms and distributed decision-making, highlighting their capabilities in decentralization, self-organization, and resilience. Based on an analysis of numerous representative cases, it is evident that Swarm Intelligence and Differential Evolution achieve significant improvements in efficiency and notable reductions in decision latency in power and traffic networks; Artificial Immune Systems strengthen the cybersecurity of critical infrastructures. Challenges remain in scalability, explainability, and ethical governance, which we address with an agenda based on federated Digital Twins and new bioinspired consensus protocols. We conclude that bioinspired algorithms not only optimize daily operations but also enable infrastructures capable of learning and recovery, laying the foundation for more sustainable and user-centered urban services.