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Calculation of minimal capacity vectors through k minimal paths under budget and time constraints

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  • Lin, Yi-Kuei

Abstract

Reducing the transmission time is an important issue for a flow network to transmit a given amount of data from the source to the sink. The quickest path problem thus arises to find a single path with minimum transmission time. More specifically, the capacity of each arc is assumed to be deterministic. However, in many real-life networks such as computer networks and telecommunication networks, the capacity of each arc is stochastic due to failure, maintenance, etc. Hence, the minimum transmission time is not a fixed number. Such a network is named a stochastic-flow network. In order to reduce the transmission time, the network allows the data to be transmitted through k minimal paths simultaneously. Including the cost attribute, this paper evaluates the probability that d units of data can be transmitted under both time threshold T and budget B. Such a probability is called the system reliability. An efficient algorithm is proposed to generate all of lower boundary points for (d, T, B), the minimal capacity vectors satisfying the demand, time, and budget requirements. The system reliability can then be computed in terms of such points. Moreover, the optimal combination of k minimal paths with highest system reliability can be obtained.

Suggested Citation

  • Lin, Yi-Kuei, 2010. "Calculation of minimal capacity vectors through k minimal paths under budget and time constraints," European Journal of Operational Research, Elsevier, vol. 200(1), pages 160-169, January.
    • Handle: RePEc:eee:ejores:v:200:y:2010:i:1:p:160-169
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    References listed on IDEAS

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    1. Yeh, Wei-Chang, 2008. "A simple minimal path method for estimating the weighted multi-commodity multistate unreliable networks reliability," Reliability Engineering and System Safety, Elsevier, vol. 93(1), pages 125-136.
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    4. Lin, Yi-Kuei, 2007. "On a multicommodity stochastic-flow network with unreliable nodes subject to budget constraint," European Journal of Operational Research, Elsevier, vol. 176(1), pages 347-360, January.
    5. Yeh, Wei-Chang, 2007. "An improved sum-of-disjoint-products technique for the symbolic network reliability analysis with known minimal paths," Reliability Engineering and System Safety, Elsevier, vol. 92(2), pages 260-268.
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    Cited by:

    1. Lin, Yi-Kuei & Yeh, Cheng-Ta, 2012. "Multi-objective optimization for stochastic computer networks using NSGA-II and TOPSIS," European Journal of Operational Research, Elsevier, vol. 218(3), pages 735-746.
    2. Calvete, Herminia I. & del-Pozo, Lourdes & Iranzo, José A., 2018. "Dealing with residual energy when transmitting data in energy-constrained capacitated networks," European Journal of Operational Research, Elsevier, vol. 269(2), pages 602-620.
    3. Niu, Yi-Feng & Lam, William H.K. & Gao, Ziyou, 2014. "An efficient algorithm for evaluating logistics network reliability subject to distribution cost," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 67(C), pages 175-189.
    4. Thi-Phuong Nguyen, 2022. "Evaluation of network reliability for stochastic-flow air transportation network considering discounted fares from airlines," Annals of Operations Research, Springer, vol. 311(1), pages 335-355, April.

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