###### Abstract
This method involves several structural parameters to perform an analysis. In RVS, visualization of parameters is needed during structural assessments, and sometimes it might be problematic due to unhealthy or old constructions. The walk-down survey, however, is prone to the evaluator's subjectivity, and therefore it is necessary to develop an Multi-criteria based RVS process and tool for screening and prioritizing buildings for further investigations. In addition, the proposed method must take into account the weight and importance of the parameters and cover the uncertainty. Consequently, a supporting decision mechanism is significant to focus on what is essential, logical, compatible, and easy to work. In that scenario, implementing a method known as 'Multi-Criteria Decision Making' would help address problems with selected parameters by involving multiple criteria [6]. From past times it can be seen that the concept of decision making is essential for resolving daily life problems, which includes different attributes and activities. Every single activity or attribute cannot resolve a scientific or mathematical approach to make a decision [7]. Multiple decisions have been taken for the majority of tasks or activities from various fields like management, engineering, politics, environment, and business, and so forth according to requirements and experience. There are many solutions available to make a perfect decision, but there would not be a single rule which can make the decision to be perfect. Hence, it needs enormous knowledge, experience, time, money, power, and many other things to make an optimal decision. Multi-Criteria Decision Making (MCDM) helps to make the best decision among several choices available according to decision-makers in every problem [8]. [PERSON] extensively used hybrid fuzzy methods such as fuzzy TOPSIS and Multiple Objective Decision Making (MODM) [9] for adequate application in regard to the emergency services in Tehran, by conducting a profound analysis based on population density, number of accidents, traffic zone, number of people per emergency, major fault lines, and regional construction to delineate the importance of the places. [PERSON] [10] assessed the vulnerability of 31 Chinese regions using 6 different MCDM methods that is, TOPSIS, VIKOR, ELECTRE III, PROMETHEE II, grey relational analysis and Weighted Sum Method (WSM) based on 11 criterion such as population, city built-up area, residential families, industries, and so forth. Out of the 6 methods, TOPSIS was the most selected method, because it was the most efficient and trustworthy one. Furthermore, [PERSON] et al. [11] used MACBETH as the MCDM method for categorizing bridges and tunnels. They prepared an additive aggregation model to calculate final priority scores, and the more the priority values, the higher the importance of the structure. Analytic Hierarchy Process (AHP) and GIS have been used by [PERSON] and [PERSON] [12] for creating vulnerability maps of the areas. [PERSON] and [PERSON] [13] proposed an MCDM framework for selecting the seismic retrofit intervention for existing reinforced concrete-frame buildings accounting for expected losses and tax incentives. The developed GIS-AHP model was unable to find a seismic vulnerability for 2 buildings because of insufficient data. [PERSON] et al. [14] studied 393 articles and 120 journals published from 2000 to 2014 on applications and methods of various MCDM techniques. Their work concluded that the AHP and hybrid MCDM are the most useful methods among individual and integrated approaches, respectively. As RVS is a discrete problem, and Multiple Attribute Decision-making (MADM) deals with discrete problems as well, few of the MADM methods were selected. Among the MADM approaches, WSM was selected due to its ease of computing and being a basic method that is suitable for single dimensional problems. WPM was selected for multi-dimensional problems, even though RVS is not multi-dimensional. AHP was selected as it is fundamentally easier compared to ELECTRE and PROMOTHEE.