Research on Collaborative Optimization Model of Complex System Reliability and System Availability

In this paper, the collaborative optimization model of complex system reliability and system availability is studied, aiming at solving the reliability and availability problems of key infrastructure such as cloud computing platform and intelligent transportation system in a highly information society. Firstly, this paper analyzes the reliability and availability characteristics of complex systems, and constructs a collaborative optimization model to achieve the optimal trade-off between system failure probability and system availability. The model selects the system’s failure probability, mean time to failure (MTTF), and mean time to repair (MTTR) as key indicators, integrating a weight coefficient to balance the importance of reliability and availability. Subsequently, this paper designs an optimization method based on Genetic Algorithm (GA), which involves encoding and initialization, fitness function calculation, selection, crossover, mutation operations, and the setting of termination conditions, to solve the model. Case studies demonstrate that through GA optimization, the system’s failure probability and availability have been significantly improved, validating the effectiveness and practicality of the model.