Bridge retrofitting is a common approach to enhance resilience of highway transportation systems. The study uses a multiobjective evolutionary algorithm to identify retrofit design configurations that are optimal with respect to resilience and retrofit cost. Application of this algorithm is demonstrated by retrofitting a bridge with column jackets and evaluating resilience of the retrofitted bridge under the multihazard effect of earthquake and flood-induced scour. Three different retrofit materials are used: steel, carbon fiber, and glass fiber composites. The inherent disparity in mechanical properties and associated costs of these different materials gives rise to a trade-off between cost and performance when it comes to retrofit operations. Results from the optimization, the Pareto near-optimal set, include solutions that are distinct from one another in terms of associated cost, contribution to resilience enhancement, and values of design parameters. This optimal set offers the best search results based on selected materials and design configurations for jackets.
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Chandrasekaran et al. (2015) studied this question.
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