Fuzzy AHP Method for Selection of a Suitable Seismic Retrofitting Alternative in Low-Rise Buildings

Abstract

Decision making for selecting an appropriate alternative among nominated alternatives is still a 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 suitable method for making a decision in order to find the best alternative considering the effective criteria in retrofitting of low-rise buildings. Analytic Hierarchy Process (AHP), as a technique of Multi-Criteria Decision Making (MCDM), is compatible to solve the problem. Effective criteria have been categorized to structural, operational, economic and functional criteria and sixteen sub-criteria considered as a pattern that satisfies the entire involved group including structural and architectural engineers, contractor, client, and authorities in retrofitting of low-rise buildings. Since most of the involved criteria such as aesthetic, durability, and compatibility have fuzzy nature and cannot be compared numerically, fuzzy AHP can be a compatible method for comparison different retrofitting alternatives among both fuzzy and non-fuzzy criteria. A matrix of pair-wise comparison (MPC) is used for determining the weight of criteria and also for scoring the alternatives respect to each criterion. A Fuzzy Importance scale with Triangular Fuzzy Numbers (TFN) is applied for comparing the criteria. The method is examined by a case study and the results show the used method can help designers for selecting the appropriate alternative.

Multi-Criteria Decision Making of Contractor Selection in Mass Rapid Transit Station Development Using Bayesian Fuzzy Prospect Model

“…Various new MCDM methods have been used in projects in different domains, especially management, engineering, and for different purposes, such as construction management and energy saving [19]. Fuzzy theory, BT, and utility theory have been widely used [8,9,11,12,18,[20][21][22][23] to select the most appropriate contractor for building projects, with each theory involving different methods for weight calculation, such as the analytical hierarchy process (AHP), WASPAS, and TOPSIS methods [1,20,[24][25][26]. Other MCDM methods, such as the AHP, ANP, MOORA, COPRAS, and SWARA-FUCOM, can also be applied to the problem [1,19,25,27].…”

“…The AHP is a technique that can be easily combined with other methods, and TOPSIS is a method that is algorithmically structured and easy to compute, especially when acting in combination with other techniques [7,10,22,35,36]. Table 1 summarizes existing MCDM techniques in the literature [1,[7][8][9][10][11][12]. The BT-based MCDM method of recalculating the criteria weights was used in a study where the quality of a school's classes was assessed.…”

“…CCPT modifies the curves of low probability and high probability in CPT [15]. The Prelec function, which is presented in the middle part of Figure 5, is usually not conformed to in BT and other relevant theories of probability in which uncertain results are expected [9]. As the decision maker considers tenders with high probability as priority contractors, the present research focused on the high-probability zone (p = 0.66-1).…”

“…This method enables decision makers to express preferences regarding a set of alternatives using the least number of judgments; the method also makes it unnecessary to examine the consistency of the decision-making process [6]. A fuzzy analytical hierarchy process (FAHP) method was used to prioritize the identified risks [7][8][9], and Fuzzy-TOPSIS achieved through the application of order preference by Similarity to Ideal Solution and fuzzy sets theory [10,11]. Second, Bayes' theorem (BT) was used as it provides a natural theoretical framework for explicitly articulating epistemic or state-of-knowledge uncertainties 2 of 32 in prior engineering knowledge.…”

AI based fuzzy MCDM models: Comparison and evaluation of dissimilar outcomes, an application to enhance pilot recruitment process

“…On the other hand, psychological traits, identified by linguistic terms, add complexity to pilot selection process. MCDM methods find broad application across various research areas such as fields compressor and equipment selection using expert opinions (Alpay & Iphar, 2018;Mardani et al, 2018;Sousa & Rocha, 2024;Taylan et al, 2016;Zhou et al, 2016), energy systems (O'Driscoll & O'Donnell, 2013;Sa et al, 2017;Taylan et al, 2020), e-commerce (Shan, 2023), and contractor (Antoniou & Aretoulis, 2019;Pashaei & Moghadam, 2018;Taylan et al, 2018), technology selection (Alcácer & Cruz-Machado, 2019;Baran-Kooiker et al, 2018;Danner et al, 2011;Ferreira et al, 2019), risk assessment (Le'sniak & Janowiec, 2019;Tamosaitiene et al, 2013;Taylan, Alidrisi, & Kabli, 2014;Taylan, Bafail, et al, 2014), workplace and its safety condition assessment (Basahel & Taylan, 2016), air traffic controller selection (Taylan, Alidrisi, & Kabli, 2014;Taylan, Bafail, et al, 2014), tourism infrastructure funding development (Skare et al, 2023), evaluating IoT platforms (Lin et al, 2020), cloud computing service selection (Mostafa, 2021), financial risk prediction (Song & Peng, 2019), parametric selection of models for an academic organization (Garg, 2022), and also applied in the aviation and aerospace industries for whilst solving problems using experts' opinion (Simsek et al, 2022). The realm of MCDM faces a primary challenge: determining optimal assessment criteria and their respective weights, complicated by the need to reconcile decision-makers' (DMs') preferences.…”