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Binary-state line assignment optimization to maximize the reliability of an information network under time and budget constraints

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  • Cheng-Ta Yeh

    (Fu Jen Catholic University)

Abstract

Information networks are critical media for various applications of cloud computing and the Internet of Things. How to maintain the system reliability of an information network is an important issue for system supervisors. The system reliability is influenced by the capacities of the lines assigned to the edges that connect the vertices of the information network, where each line should operate to provide a certain capacity or fail. This study aims to maximize the system reliability of an information network by determining the optimal binary-state line assignment under an assignment budget constraint. In contrast to previous studies related to system reliability maximization, this study considers a time threshold in system reliability evaluation. In addition, the information network is regarded as a stochastic information network, as each edge may include several binary-state lines and provide multiple states. A method based on minimal paths and genetic algorithm (GA) with elite replacement is developed to evaluate the system reliability and search for the optimal solution. Several numerical experiments are conducted to show that the GA not only determines the exact solution but also exhibits higher computational efficiency than several well-known meta-heuristic algorithms.

Suggested Citation

  • Cheng-Ta Yeh, 2020. "Binary-state line assignment optimization to maximize the reliability of an information network under time and budget constraints," Annals of Operations Research, Springer, vol. 287(1), pages 439-463, April.
    • Handle: RePEc:spr:annopr:v:287:y:2020:i:1:d:10.1007_s10479-019-03405-w
    DOI: 10.1007/s10479-019-03405-w
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    References listed on IDEAS

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    1. Lin, Yi-Kuei & Yeh, Cheng-Ta, 2012. "Determining the optimal double-component assignment for a stochastic computer network," Omega, Elsevier, vol. 40(1), pages 120-130, January.
    2. Xiang, Shihu & Yang, Jun, 2018. "Performance reliability evaluation for mobile ad hoc networks," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 32-39.
    3. Yeh, Cheng-Ta & Fiondella, Lance, 2017. "Optimal redundancy allocation to maximize multi-state computer network reliability subject to correlated failures," Reliability Engineering and System Safety, Elsevier, vol. 166(C), pages 138-150.
    4. Ramirez-Marquez, José Emmanuel & Rocco S., Claudio M., 2009. "Stochastic network interdiction optimization via capacitated network reliability modeling and probabilistic solution discovery," Reliability Engineering and System Safety, Elsevier, vol. 94(5), pages 913-921.
    5. Kim, Heungseob & Kim, Pansoo, 2017. "Reliability–redundancy allocation problem considering optimal redundancy strategy using parallel genetic algorithm," Reliability Engineering and System Safety, Elsevier, vol. 159(C), pages 153-160.
    6. Climaco, Joao C.N. & Pascoal, Marta M.B. & Craveirinha, Jose M.F. & Captivo, M. Eugenia V., 2007. "Internet packet routing: Application of a K-quickest path algorithm," European Journal of Operational Research, Elsevier, vol. 181(3), pages 1045-1054, September.
    7. James, Tabitha & Rego, Cesar & Glover, Fred, 2009. "A cooperative parallel tabu search algorithm for the quadratic assignment problem," European Journal of Operational Research, Elsevier, vol. 195(3), pages 810-826, June.
    8. Hiramatsu, Tomoru & Inoue, Hiroki & Kato, Yasuhiko, 2016. "Estimation of interregional input–output table using hybrid algorithm of the RAS method and real-coded genetic algorithm," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 95(C), pages 385-402.
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    Cited by:

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