Optimization of Complex System Reliability using Hybrid Grey Wolf Optimizer


  • Ganga Negi Department of Mathematics, Graphic Era Deemed to be University, Dehradun, India
  • Anuj Kumar Department of Mathematics, University of Petroleum and Energy Studies, Dehradun, India
  • Sangeeta Pant Department of Mathematics, University of Petroleum and Energy Studies, Dehradun, India
  • Mangey Ram Department of Mathematics, Computer Science and Engineering, Graphic Era, Dehradun, India




Cost function, Metaheuristics, Reliability allocation problems, Particle Swarm Optimization (PSO), Grey Wolf Optimizer (GWO), Hybrid PSO-GWO algorithm (HPSOGWO).


Reliability allocation to increase the total reliability has become a successful way to increase the efficiency of the complex industrial system designs. A lot of research in the past have tackled this problem to a great extent. This is evident from the different techniques developed so far to achieve the target. Stochastic metaheuristics like simulated annealing, Tabu search (TS), Particle Swarm Optimization (PSO), Cuckoo Search Optimization (CS), Genetic Algorithm (GA), Grey wolf optimization technique (GWO) etc. have been used in recent years. This paper proposes a framework for implementing a hybrid PSO-GWO algorithm for solving some reliability allocation and optimization problems. A comparison of the results obtained is done with the results of other well-known methods like PSO, GWO, etc. The supremacy/competitiveness of the proposed framework is demonstrated from the numerical experiments. These results with regard to the time taken for the computation and quality of solution outperform the previously obtained results by the other well-known optimization methods.


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How to Cite

Negi, G., Kumar, A., Pant, S., & Ram, M. (2021). Optimization of Complex System Reliability using Hybrid Grey Wolf Optimizer. Decision Making: Applications in Management and Engineering, 4(2), 241–256. https://doi.org/10.31181/dmame210402241n