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MILP Models for Complex System Reliability Redundancy Allocation with Mixed Components

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  • Young Woong Park

    (Ivy College of Business, Iowa State University, Ames, Iowa 50011)

Abstract

The redundancy allocation problem (RAP) aims to find an optimal allocation of redundant components subject to resource constraints. In this paper, mixed integer linear programming (MILP) models and MILP-based algorithms are proposed for complex system reliability redundancy allocation problem with mixed components, where the system have bridges or interconnecting subsystems and each subsystem can have mixed types of components. Unlike the other algorithms in the literature, the proposed MILP models view the problem from a different point of view and approximate the nonconvex nonlinear system reliability function of a complex system using random samples. The solution to the MILP converges to the optimal solution of the original problem as sample size increases. In addition, data aggregation-based algorithms are proposed to improve the solution time and quality based on the proposed MILP models. A computational experiment shows that the proposed models and algorithms converge to the optimal or best-known solution as sample size increases. The proposed algorithms outperform popular metaheuristic algorithms in the literature.

Suggested Citation

  • Young Woong Park, 2020. "MILP Models for Complex System Reliability Redundancy Allocation with Mixed Components," INFORMS Journal on Computing, INFORMS, vol. 32(3), pages 600-619, July.
    • Handle: RePEc:inm:orijoc:v:32:y:3:i:2020:p:600-619
    DOI: 10.1287/ijoc.2019.0895
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    References listed on IDEAS

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    Cited by:

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    2. Zhang, Hanxiao & Li, Yan-Fu, 2022. "Robust optimization on redundancy allocation problems in multi-state and continuous-state series–parallel systems," Reliability Engineering and System Safety, Elsevier, vol. 218(PA).

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