Modified wild horse optimizer based approach for solving constraint reliability redundancy optimization problems
Abstract
The Reliability Redundancy Allocation Problem (RRAP) is a complex optimization problem that involves determining the optimal deployment of redundant components to enhance overall system performance. Exact approaches can be computationally expensive and time-consuming for large-scale tasks due to the combinatorial nature of the problem. This article employs a modified version of the recently developed population-based metaheuristic called "Wild Horse Optimization" to optimize the RRAP problem subject to nonlinear constraints. Three RRAP standard benchmark problems have been taken into consideration, and a modified WHO (MWHO) was employed to determine the optimal allocation of redundant components. This research demonstrates that MWHO outperforms current meta-heuristic methods and is a promising approach for solving RRAP.