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A novel minimal cut-based algorithm to find all minimal capacity vectors for multi-state flow networks

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  • Huang, Ding-Hsiang
  • Huang, Cheng-Fu
  • Lin, Yi-Kuei

Abstract

Real systems, such as computer systems, can be modeled as network topologies with vertices and edges. Owing to equipment failures and maintenance requirements, the capacities of edges have several states. Such systems are regarded as multi-state flow networks (MSFN). System reliability of an MSFN is the probability that the required flow (i.e., demand) can successfully be sent from the source to the sink. By adopting a minimal path (MP) approach, system reliability can be computed in terms of all minimal capacity vectors meeting the demand d. A minimal capacity vector is called a d-MP. Although several algorithms have been presented in the literature for finding all d-MP, improving efficiency in the search for all d-MP is always a challenge. A group approach with both the concepts of minimal cut and MP is developed in this study, narrowing the search range of feasible flow vectors. An algorithm based on the group approach is then proposed to improve the efficiency of the d-MP search. According to the structure of the proposed algorithm, parallel computing can be implemented with significant improvement in the efficiency of the d-MP generation, where the proposed algorithm is compared with previous ones based on three benchmarks, in terms of CPU time.

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  • Huang, Ding-Hsiang & Huang, Cheng-Fu & Lin, Yi-Kuei, 2020. "A novel minimal cut-based algorithm to find all minimal capacity vectors for multi-state flow networks," European Journal of Operational Research, Elsevier, vol. 282(3), pages 1107-1114.
    • Handle: RePEc:eee:ejores:v:282:y:2020:i:3:p:1107-1114
    DOI: 10.1016/j.ejor.2019.10.030
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    1. Sebastio, Stefano & Trivedi, Kishor S. & Wang, Dazhi & Yin, Xiaoyan, 2014. "Fast computation of bounds for two-terminal network reliability," European Journal of Operational Research, Elsevier, vol. 238(3), pages 810-823.
    2. Liu, Yu & Chen, Yiming & Jiang, Tao, 2018. "On sequence planning for selective maintenance of multi-state systems under stochastic maintenance durations," European Journal of Operational Research, Elsevier, vol. 268(1), pages 113-127.
    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. Majid Forghani-elahabad & Nelson Kagan, 2019. "Reliability evaluation of a stochastic-flow network in terms of minimal paths with budget constraint," IISE Transactions, Taylor & Francis Journals, vol. 51(5), pages 547-558, May.
    5. Yeh, Cheng-Ta, 2019. "An improved NSGA2 to solve a bi-objective optimization problem of multi-state electronic transaction network," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    6. Bai, Guanghan & Zuo, Ming J. & Tian, Zhigang, 2015. "Search for all d-MPs for all d levels in multistate two-terminal networks," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 300-309.
    7. Cheng-Fu Huang, 2019. "Evaluation of system reliability for a stochastic delivery-flow distribution network with inventory," Annals of Operations Research, Springer, vol. 277(1), pages 33-45, June.
    8. Yeh, Wei-Chang & Chu, Ta-Chung, 2018. "A novel multi-distribution multi-state flow network and its reliability optimization problem," Reliability Engineering and System Safety, Elsevier, vol. 176(C), pages 209-217.
    9. Yan, Zhou & Qian, Meng, 2007. "Improving efficiency of solving d-MC problem in stochastic-flow network," Reliability Engineering and System Safety, Elsevier, vol. 92(1), pages 30-39.
    10. Jane, Chin-Chia & Laih, Yih-Wenn, 2017. "Distribution and reliability evaluation of max-flow in dynamic multi-state flow networks," European Journal of Operational Research, Elsevier, vol. 259(3), pages 1045-1053.
    11. Jane, Chin-Chia & Laih, Yih-Wenn, 2010. "A dynamic bounding algorithm for approximating multi-state two-terminal reliability," European Journal of Operational Research, Elsevier, vol. 205(3), pages 625-637, September.
    12. Niu, Yi-Feng & Gao, Zi-You & Lam, William H.K., 2017. "A new efficient algorithm for finding all d-minimal cuts in multi-state networks," Reliability Engineering and System Safety, Elsevier, vol. 166(C), pages 151-163.
    13. Xiu-Zhen Xu & Yi-Feng Niu & Qing Li, 2018. "Performance Assessment of a Freight Network with Stochastic Capacities," Complexity, Hindawi, vol. 2018, pages 1-9, September.
    14. Tian, Zhigang & Levitin, Gregory & Zuo, Ming J., 2009. "A joint reliability–redundancy optimization approach for multi-state series–parallel systems," Reliability Engineering and System Safety, Elsevier, vol. 94(10), pages 1568-1576.
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    Cited by:

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    3. Zhang, Hanxiao & Sun, Muxia & Li, Yan-Fu, 2022. "Reliability–redundancy allocation problem in multi-state flow network: Minimal cut-based approximation scheme," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
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    5. Yeh, Cheng-Ta & Lin, Yi-Kuei & Yeng, Louis Cheng-Lu & Huang, Pei-Tzu, 2021. "Reliability evaluation of a multistate railway transportation network from the perspective of a travel agent," Reliability Engineering and System Safety, Elsevier, vol. 214(C).

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