Elena Nechita
Vasile Alecsandri University, Bacău, Romania

During the last decades, the community of researchers from various domains has shown a growing interest towards systems resilience. Obviously, systems of any kind are expected to meet requirements and maintain their operational characteristics as long as possible, while facing changing (sometimes unpredictable) conditions, environments and/or challenges. The concept of resilience has emerged for complex, dynamic systems and can be generally defined as the capacity of a system to tolerate disturbances while retaining its structure and functions. The list of domains where systems resilience is important is long and specific definitions have been provided: engineering, economics, environment, ecology, psychology and neurobiology, sociology. In computer science, resilience has been defined mainly for networks and large scale distributed systems, security and soft infrastructure systems. Given the wide interest and importance of the concept, not only for researchers but for policymakers too, numerous and sometimes diverging interpretations and perceptions have been proposed for resilience. Several studies proposed conceptual and theoretical models for resilience, such as for societal resilience, for disaster risk management or for high-performance computing systems. Our paper presents several considerations on the resilience of a nature-inspired class of algorithms, namely the Ant Colony Optimization heuristic algorithms.