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Quick Estimation of Network Performance Measures Using Associative Memory Techniques

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  • Naga, Palavadi
  • Fan, Yueyue

Abstract

Many important decision making processes in transportation planning and engineering involve repetitive computation of network performance, measured by total network delay, throughput, network efficiency, etc. The computational complexity imposed by repetitive evaluation of these measures, especially under user equilibrium condition, is a serious obstacle for timely decision making regarding transportation networks. This study applies Associative Memory (AM) techniques, which are conceptually and computationally simple, to quick estimation of these performance measures. The results of the numerical experiments were encouraging and the relative error on an average was found to be less than two percent. Furthermore, the applicability of this approximation method to bilevel network problems is explored through a study on the network recovery problem (NRP), which seeks a quick and effective repairing strategy for disturbed networks following natural or human-induced disasters.

Suggested Citation

  • Naga, Palavadi & Fan, Yueyue, 2008. "Quick Estimation of Network Performance Measures Using Associative Memory Techniques," Institute of Transportation Studies, Working Paper Series qt8hd526wh, Institute of Transportation Studies, UC Davis.
    • Handle: RePEc:cdl:itsdav:qt8hd526wh
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    References listed on IDEAS

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    3. Kalaba, R. & Lichtenstein, Z. & Tesfatsion, L., 1989. "Linear And Nonlinear Associative Memories For Parameter Estimation," Papers m8913, Southern California - Department of Economics.
    4. Réka Albert & Hawoong Jeong & Albert-László Barabási, 2000. "Error and attack tolerance of complex networks," Nature, Nature, vol. 406(6794), pages 378-382, July.
    5. Yang, Hai & Bell, Michael G. H., 2001. "Transport bilevel programming problems: recent methodological advances," Transportation Research Part B: Methodological, Elsevier, vol. 35(1), pages 1-4, January.
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    Cited by:

    1. Milad Zamanifar & Seyed Mohammad Seyedhoseyni, 2017. "Recovery planning model for roadways network after natural hazards," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 87(2), pages 699-716, June.

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