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- W2029184015 abstract "Pavement maintenance planning and programming requires optimization analysis involving multiobjective considerations. Traditionally single-objective optimization techniques have been employed by pavement researchers and practitioners because of the complexity involved in multiobjective analysis. This paper develops a genetic-algorithm-based procedure for solving multiobjective network level pavement maintenance programming problems. The concepts of Pareto optimal solution set and rank-based fitness evaluation, and two methods of selecting an optimal solution, were adopted. It was found that the robust search characteristics and multiple-solution handling capability of genetic-algorithms were well suited for multiobjective optimization analysis. Formulation and development of the solution algorithm were described and demonstrated with a numerical example problem in which a hypothetical network level pavement maintenance programming analysis was performed for two- and three-objective optimization, respectively. A comparison between the two- and three-objective solutions was made to highlight some practical considerations in applying multiobjective optimization to pavement maintenance management." @default.
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- W2029184015 date "2000-09-01" @default.
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- W2029184015 title "Multiobjective Optimization for Pavement Maintenance Programming" @default.
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- W2029184015 doi "https://doi.org/10.1061/(asce)0733-947x(2000)126:5(367)" @default.
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