Reliability Assessment of Highway Bridges Based on Combined Empowerment–TOPSIS Method

Abstract

(1) In recent years, with the continuous increase of the state’s investment in infrastructure, the construction of highways and bridges has developed rapidly, which has brought great convenience to people’s lives. At the same time, with the increase of bridge service time, the reliability of bridges declines. In order to meet the requirements of sustainable development, it is necessary to accurately evaluate the reliability of bridges. However, most of the existing evaluation methods have single-weighting and one-sidedness. There are problems such as strong subjectivity and overly simple evaluation procedures. Therefore, it is urgent to establish a new scientific bridge reliability evaluation system. (2) Methods. In this paper, a bridge superstructure is taken as the research object, and the “Technical Condition Assessment Standard for Highway Bridges” (JTG/T H21-2011) is used as the criterion to establish a bridge reliability evaluation index system. The subjective and objective weights of the evaluation indicators are based on minimum discriminant information. Each evaluation indicator is combined and weighted; then, the closeness of each evaluation object to the positive ideal solution is determined according to Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). Finally, the reliability level of each evaluation object is determined. (3) Results. Reliability evaluation of the three-span superstructure of the bridge was carried out, and final reliability evaluation results of “Grade 2, Grade 2, Grade 2” were obtained, which are consistent with the actual working state of the bridge. (4) Conclusions. The evaluation results of this paper are consistent with the results obtained by the traditional AHP–Extenics method, but the evaluation model of this paper adopts combined weighting, which avoids the one-sidedness of the weighting of a single method—thus, the comprehensive weight obtained not only reflects the subjective intention of decision makers, but also reflects the objective properties of the data.