Reliability-redundancy allocation Problem of a queueing system considering energy consumption

Document Type : Article

Authors

1 Faculty of Industrial Engineering, Urmia University of Technology, Band Ave., Urmia, Iran, 57166-17165

2 Department of Information Technology and Decision Sciences, G. Brint Ryan College of Business, University of North Texas, Denton, Texas, USA, 76203-5017

Abstract

In Reliability Redundancy Allocation Problem (RRAP), the reliability and redundancy of components in a given system configuration are determined while concerning some problem-specific constraints. RRAP can be applied to various industries. Moreover, queueing systems are among the most common systems in the manufacturing and service industries. Failure in queueing systems can result in unwanted severe damages. Reliability analysis of queueing systems should be undertaken concerning their performance measures. Therefore, an RRAP of a queueing system considering queueing costs is studied in this article. The proposed cost function includes queueing, repair, and energy consumption costs. A memetic algorithm is used to obtain optimal redundancy and failure rates of components and the system’s service rate, which affects the energy consumption level. Extensive numerical experiments and sensitivity analyses are performed to present the problem’s applicability and the proposed algorithm.

Keywords

References

  1. References:

    1. Teimouri, M., A. Zaretalab, S.T.A. Niaki, et al., "An efficient memory-based electromagnetism-like mechanism for the redundancy allocation problem", Applied Soft Computing, 38, pp. 423-436 (2016).
    2. Sharifi, M., M. Saadvandi, and M. Shahriari, "Presenting a series-parallel redundancy allocation problem with multi-state components using recursive algorithm and meta-heuristic", Scientia Iranica, 27(2), pp. 970-982 (2020).
    3. Yeh, W.-C. and T.-J. Hsieh, "Solving reliability redundancy allocation problems using an artificial bee colony algorithm", Computers & Operations Research, 38(11), pp. 1465-1473 (2011).
    4. Kanagaraj, G., S. Ponnambalam, and N. Jawahar, "A hybrid cuckoo search and genetic algorithm for reliability–redundancy allocation problems", Computers & Industrial Engineering, 66(4), pp. 1115-1124 (2013).
    5. Sabri-Laghaie, K., M. Eshkevari, M. Fathi, et al., "Redundancy allocation problem in a bridge system with dependent subsystems", Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, 233(4), pp. 658-669 (2019).
    6. Garg, H. and S. Sharma, "Multi-objective reliability-redundancy allocation problem using particle swarm optimization", Computers & Industrial Engineering, 64(1), pp. 247-255 (2013).
    7. Sabri-Laghaie, K. and M. Karimi-Nasab, "Random search algorithms for redundancy allocation problem of a queuing system with maintenance considerations", Reliability Engineering & System Safety, 185, pp. 144-162 (2019).
    8. Najafi, A., H. Karimi, A. Chambari, et al., "Two metaheuristics for solving the reliability redundancy allocation problem to maximize mean time to failure of a series–parallel system", Scientia Iranica, 20(3), pp. 832-838 (2013).
    9. Roy, P., B. Mahapatra, G. Mahapatra, et al., "Entropy based region reducing genetic algorithm for reliability redundancy allocation in interval environment", Expert systems with applications, 41(14), pp. 6147-6160 (2014).
    10. Kim, H. and P. Kim, "Reliability–redundancy allocation problem considering optimal redundancy strategy using parallel genetic algorithm", Reliability Engineering & System Safety, 159, pp. 153-160 (2017).
    11. Sharifi, M. and S. Taghipour, "Optimizing a redundancy allocation problem with open-circuit and short-circuit failure modes at the component and subsystem levels", Engineering Optimization, pp. 1-17 (2020).
    12. Pourkarim Guilani, P., A. Zaretalab, S. A Niaki, et al., "A bi-objective model to optimize reliability and cost of k-out-of-n series-parallel systems with tri-state components", Scientia Iranica, 24(3), pp. 1585-1602 (2017).
    13. Ouyang, Z., Y. Liu, S.-J. Ruan, et al., "An improved particle swarm optimization algorithm for reliability-redundancy allocation problem with mixed redundancy strategy and heterogeneous components", Reliability Engineering & System Safety, 181, pp. 62-74 (2019).
    14. Huang, C.-L., "A particle-based simplified swarm optimization algorithm for reliability redundancy allocation problems", Reliability Engineering & System Safety, 142, pp. 221-230 (2015).
    15. Zhang, E. and Q. Chen, "Multi-objective reliability redundancy allocation in an interval environment using particle swarm optimization", Reliability Engineering & System Safety, 145, pp. 83-92 (2016).
    16. Hsieh, T.-J., "A simple hybrid redundancy strategy accompanied by simplified swarm optimization for the reliability–redundancy allocation problem", Engineering Optimization, pp. 1-18 (2021).
    17. Garg, H., M. Rani, and S. Sharma, "An efficient two phase approach for solving reliability–redundancy allocation problem using artificial bee colony technique", Computers & operations research, 40(12), pp. 2961-2969 (2013).
    18. Hsieh, Y.C. and P.S. You, "An effective immune based two-phase approach for the optimal reliability–redundancy allocation problem", Applied Mathematics and Computation, 218(4), pp. 1297-1307 (2011).
    19. Garg, H., "An efficient biogeography based optimization algorithm for solving reliability optimization problems", Swarm and Evolutionary Computation, 24, pp. 1-10 (2015).
    20. Mousavi, S.M., N. Alikar, and S.T.A. Niaki, "An improved fruit fly optimization algorithm to solve the homogeneous fuzzy series–parallel redundancy allocation problem under discount strategies", Soft Computing, 20(6), pp. 2281-2307 (2016).
    21. Maksoud, E.Y.A. and M.S. Moustafa, "A semi-Markov decision algorithm for the optimal maintenance of a multistage deteriorating two-unit standby system", Operational Research, 9(2), pp. 167-182 (2009).
    22. Juybari, M.N., M. Abouei Ardakan, and H. Davari-Ardakani, "A penalty-guided fractal search algorithm for reliability–redundancy allocation problems with cold-standby strategy", Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, 233(5), pp. 775-790 (2019).
    23. Dobani, E.R., M.A. Ardakan, H. Davari-Ardakani, et al., "RRAP-CM: A new reliability-redundancy allocation problem with heterogeneous components", Reliability Engineering & System Safety, 191, pp. 106563 (2019).
    24. Azimi, P., M. Hemmati, and A. Chambari, "Solving the redundancy allocation problem of k-out-of-n with non-exponential repairable components using optimization via simulation approach", Scientia Iranica, 24(3), pp. 1547-1560 (2017).
    25. Sharifi, M., M. Shahriyari, A. Khajepour, et al., "Reliability Optimization of a k-out-of-n Series-Parallel System with Warm Standby Components", Scientia Iranica, (2021).
    26. Neuts, M.F., Matrix-geometric solutions in stochastic models: an algorithmic approach. 1981: Dover Pubns.
    27. Buchholz, P., J. Kriege, and I. Felko, Input modeling with phase-type distributions and Markov models: theory and applications. 2014: Springer.
    28. Medhi, J., Stochastic models in queueing theory. 2002: Elsevier.
    29. Gendreau, M. and J.-Y. Potvin, Handbook of metaheuristics. Vol. 2. 2010: Springer.
    30. Liu, B. and B. Liu, Theory and practice of uncertain programming. Vol. 239. 2009: Springer.
    31. Salimi, H., "Stochastic fractal search: a powerful metaheuristic algorithm", Knowledge-Based Systems, 75, pp. 1-18 (2015).
    32. Kuo, W. and V.R. Prasad, "An annotated overview of system-reliability optimization", IEEE Transactions on reliability, 49(2), pp. 176-187 (2000).
    33. Kazemisaboor, A., A. Aghaie, and H. Salmanzadeh, "A simulation-based optimisation framework for process plan generation in reconfigurable manufacturing systems (RMSs) in an uncertain environment", International Journal of Production Research, pp. 1-19 (2021).
Scientia Iranica

Articles in Press, Accepted Manuscript
Available Online from 16 May 2022

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