In a highway asset maintenance management system involving more than one highway asset type, identifying an equitable optimal allocation of available budget to individual asset systems is a major challenge. This is because the following outcomes are desirable: (1) the maintenance needs of all assets are adequately addressed, (2) the objectives of individual asset systems are optimally satisfied in an equitable manner, and (3) the objectives of the overall highway asset system are achieved optimally. To achieve these desirable outcomes, this paper proposes a two-stage approach in solving the dual-level multiasset, multiobjective pavement network maintenance optimal budget allocation problem. Stage I of the approach analyzes the individual multiobjective asset systems independently to establish for each a family of optimal Pareto solutions. Minimization of maintenance cost is selected as a common objective for the individual asset systems. This serves as the link for interaction with the Stage II analysis. Stage II adopts an optimal algorithm to allocate budget to individual assets by performing a cross-asset trade-off to achieve the optimal budget solution for the given overall system-level objectives. By defining a minimum performance threshold level for each asset type, the Stage II optimization analysis aims to achieve an equitable allocation of budget by maintaining equivalent amounts of performance improvements for the individual asset systems above their respective minimum threshold levels. The conceptual framework of the proposed approach is presented in this paper with a numerical example to illustrate the detailed working of the procedure.


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    Title :

    Optimal Multiasset Maintenance Budget Allocation in Highway Asset Management


    Contributors:
    Fwa, T. F. (author) / Farhan, J. (author)

    Published in:

    Publication date :

    2012-02-13


    Size :

    92012-01-01 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



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