Modified wild horse optimizer based approach for solving constraint reliability redundancy optimization problems

  • Anuj Kumar School of Computer Science Engineering \& Applications, D. Y. Patil International University (DYPIU), Akrudi, Pune 411044, Maharashtra, India.
  • Tina Sharma Department of Mathematics, University of Petroleum \& Energy Studies, Dehradun 248007, India.
  • Manoj K. Singh School of Computer Science Engineering and Technology, Bennett University, Greater Noida, 201310, India.
  • Sangeeta Pant Department of Applied Sciences, Symbiosis Institute of Technology, Symbiosis International (Deemed University) (SIU), Lavale, Pune 412115, Maharashtra, India
  • Shshank Chaube Department of Physical Sciences, Jaypee University Anoopshahr, Bulandshahr, 203390, India.
  • Mangey Ram Department of Mathematics, Computer Science and Engineering, Graphic Era Deemed to be University, Dehradun, Uttarakhand, India.


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.