A multi-attribute approach to select the best method for repairing river bridge columns

Salmaninezhad, M and Jazayeri Moghaddas, S M (2023) A multi-attribute approach to select the best method for repairing river bridge columns. Engineering, Construction and Architectural Management, 30(1), pp. 1-18. ISSN 09699988

Abstract

Purpose: Pier scour is one of the main causes of damage to the columns of the river bridges. It is essential to select the best method among various repair methods based on different evaluation indices. However, there is no procedure for ranking these repair methods based on their attributes. The present study seeks to set an approach for this ranking. Design/methodology/approach: In this paper, a multi-attribute decision-making (MADM) model is presented for ranking the repair techniques, in which alternatives are examined using the most important evaluation criteria. In addition, a combination of entropy and eigenvector methods has been proposed for weighting these attributes. A case study is then used to demonstrate the applicability and the validity of the method. Findings: The execution of the model using two multi-criteria methods yielded similar results, which confirms its accuracy and precision. Moreover, the research findings showed the consistency of the objective and subjective weighting methods and the conformity of the weights obtained for the attributes from the combination of these methods to the nature of the problem. Originality/value: The selection of the proper method for repairing the bridge columns plays an essential role in success of the bridge restoration. The proposed model introduces an approach for ranking repair methods and selecting the best one that has not been presented so far. Also, the weighing method for attributes is an innovative method for ranking restoration methods that has been proven in a case study.

Item Type: Article
Uncontrolled Keywords: attribute; madm; repairing method; river bridge columns; weighting
Date Deposited: 11 Apr 2025 15:13
Last Modified: 11 Apr 2025 15:13