Solving Reliability-Redundancy Allocation Problems using Grasshopper Optimization Algorithm

Success of companies and satisfaction of customers heavily depend on system reliability performance. System design improvements and higher efficiency exist directly from the proper distribution of reliability overhead resources. The extensive application domain of Reliability Redundancy Allocation Problems (RRAPs) includes fundamental challenges in various real-life situations such as software design along with cost optimization and development. The system reliability optimization problem is recognized as NP-Hard, and its resolution demands planned and effective solution approaches since there doesn’t exist a polynomial-time method for finding optimal solutions. This research utilizes Grasshopper Optimization (GOA) due to its ability to solve complex constrained optimization problems effectively and its high accuracy in obtaining good solutions. Eight system reliability block diagrams were used, varying in their difficulty from simple to complex problems. Results showed that system reliability comprised a significant increase when GOA-based optimization was applied compared to other algorithms. GOA achieved higher performance using the eight system reliability block diagrams, and its results validated both the efficiency and the solution-delivering capabilities of the algorithm for enhancing overall software reliability.