High systems’ reliability is crucial in competitive industrial plants. System Reliability-Redundancy Allocation (RRA) is an essential design consideration for maximizing the overall systems’ reliability under various systems’ constraints. This paper addresses the system RRAP problem by investigating two effective nature-inspired optimization techniques, namely Particle Swarm Optimization (PSO) and Grey Wolf Optimizer (GWO), implemented with penalty functions. Their capability in solving the RRA problem is evaluated regarding a system consisting of fifteen subsystems connected in series. Results show that the PSO is a better approach to solving this problem than the GWO. © 2022