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Random search algorithms for redundancy allocation problem of a queuing system with maintenance considerations

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  • Sabri-Laghaie, Kamyar
  • Karimi-Nasab, Mehdi

Abstract

The Redundancy Allocation Problem (RAP) is becoming all the time more important in system reliability design. Therefore, RAP has been studied vastly for different systems and under various assumptions. One of the important systems that RAP can be applied to them is queuing systems. In many applications, reliability of queuing systems need to be improved with regard to some queuing and reliability cost constraints. Despite the importance of queuing systems in real world situations, RAP of these systems have not gained attention in the literature. Therefore, RAP of a queuing system with maintenance considerations and including queueing costs in the modeling of RAP is considered in this paper. To find optimal solutions of the problem, four random search algorithms are developed and compared based on the problem structures. According to the experiments, for unimodal solution spaces algorithms 1 and 2 and for multimodal solution spaces algorithms 3 and 4 are recommended.

Suggested Citation

  • Sabri-Laghaie, Kamyar & Karimi-Nasab, Mehdi, 2019. "Random search algorithms for redundancy allocation problem of a queuing system with maintenance considerations," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 144-162.
    • Handle: RePEc:eee:reensy:v:185:y:2019:i:c:p:144-162
    DOI: 10.1016/j.ress.2018.12.010
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    References listed on IDEAS

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    Cited by:

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    2. Tian, Yuan & Han, Minghao & Kulkarni, Chetan & Fink, Olga, 2022. "A prescriptive Dirichlet power allocation policy with deep reinforcement learning," Reliability Engineering and System Safety, Elsevier, vol. 224(C).

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