Multi-criteria decision framework for seismic retrofitting of low-rise buildings

Abstract

Among different types of old buildings in earthquake prone area, many conventional low-rise buildings are vulnerable due to non-compliance with current codes and other potential weaknesses. Therefore, decision making for selecting an appropriate alternative is still an unresolved problem among retrofit designers. It is clear that selected alternative, should comply the current codes in terms of structural criteria, but the other criteria may not be considered. The main goal of this study is to introduce a new methodology for making decision in order to find the best alternative considering all effective criteria in retrofitting of low-rise buildings. Among several engineering algorithms which have been studied in this research, Analytic Hierarchy Process (AHP), as a technique of Multi-Criteria Decision Making (MCDM), found compatible to solve the problem. Considering four main criteria and nineteen sub-criteria under a hierarchy pattern can satisfy all involved parties in retrofitting projects. Using Matrix of Pair-Wise Comparison (MPC) as a technique of AHP for determining the weight of the criteria will be difficult when the number of judgment becomes large. For solving this problem, default weights as a reliable method for determining the weight were provided through the questionnaires. Besides the quantitative method, in order to score the alternatives, verbal rating was proposed as a qualitative method which is the focus of this research. Based on the above framework, a computer program was developed and using qualitative and quantitative methods, solving MPCs, calculating Consistency Ratio (CR), and normalization of the results are the capability of the program. The program was also evaluated through two case studies and the results verify that the program can help decision makers to select an appropriate alternative. Fuzzy AHP proposed as a developed method and the first case study was also evaluated by Triangular Fuzzy Numbers (TFN) and the results conclusion with AHP.