Bridges, mainly exposed in a multiple hazard environment, are the most vulnerable component of the road network. Damage of critical bridge components (i.e., piers, bearings, and abutments) may result in loss of bridge functionality after a hazard event and, therefore, the rapid decision for the most appropriate retrofit measure is crucial in order to limit the related direct and indirect losses in short time after the event. In line with the above, a holistic methodology is proposed herein for the selection of the optimum retrofit measure for bridge piers, among reinforced concrete or FRP jackets. The proposed methodology is based on advanced, inelastic analysis results, multi-objective optimization techniques and genetic algorithms to derive the retrofit measure's properties in order to meet selected performance, cost and sustainability criteria. Based on literature recommendations, the common practice is to select the retrofit measure on the basis of the seismic assessment results and, in particular, the fragility curves of bridges retrofitted with various schemes (i.e., reinforced concrete, steel, or FRP jackets) and varying properties. However, a component-specific selection of the optimum retrofit measure properties is proposed herein, also accounting for the as-built properties of the bridge pier studied and the targeted performance, cost and CO2 emissions criteria. The source code developed for applying the proposed approach is also provided (in Github). Since both the components and the criteria are parametrically defined within the code, it could be practically used for different case studies, investigating the effect of as-built properties, retrofit measure properties, and selection criteria on the results. The proposed methodology is indicatively applied to a case study bridge pier, estimating the optimal retrofit measure among RC and FRP jackets and its properties for selected performance, cost, and sustainability criteria, comparatively assessing the results.