Fuzzy Analytic Hierarchy Process (FAHP) with Cosine Consistency Index for Coastal Erosion Problem: A Case Study of Setiu Wetlands

Abstract

Decision making is the process of selecting the best choice out of multiple alternatives and multiple factors to be considered. Decision making which involves human judgments is always imprecise and subjective. Fuzzy AHP has been introduced to cater those deficiencies in traditional AHP. One of the vital issues in Fuzzy AHP is the consistency measure. The studies in that problem has been explored by many scholars, however, many applications still ignore the consistency measure in their works. Therefore, this paper aims to introduce the Cosine Consistency Index (CCI) proposed by Kou and Lin into Fuzzy AHP. The proposed methodology is applied to the case study of Setiu Wetlands coastal areas in Setiu, Terengganu to weight the factors of coastal erosion. The obtained results show that land use/cover change (17.4%) is the most contributing factor towards the coastal erosion. It is followed by sea area class (14%), erodibility (11%), population density (10.1%), shoreline evolution (9.9%), sedimentary discharge (8.7%), tidal range (7.2%), storm surge (7.1%), wave height (4.9%), budgetary revenue of local government (3.6%), relative sea level (3.3%) and coastal protection (2.8%). The proposed methodology is applicable to many other decision making problems. The applied cosine consistency index into the Fuzzy AHP evaluation process makes the obtained results more plausible and convincing.

Decision analysis of warehouse productivity performance indicators to enhance logistics operational efficiency

“…Equation (2) depicts the pair-wise contribution matrix, where dij k˜ denotes the kth decision maker's choice for the ith criterion over jth criterion and the “tilde” denotes the triangular number (Buckley, 1985). As a result, Awang et al (2017) summarized the Triangular Fuzzy Numbers are denoted as truedij k˜=(l,m,u).…”

“…The AHP survey is typically performed using an expert-based approach that is qualified to provide representative findings due to the detailed interpretation that includes many facets and viewpoints of an issue (Opitz et al, 2019). However, every AHP-related method's final judgment is only plausible if the pairwise comparison matrices pass the accuracy checks (Awang et al, 2017). As a result, an extension approach from AHP to the fuzzy domain is used in this analysis.…”

“…Equation ( 2) depicts the pair-wise contribution matrix, where f d k ij denotes the k th decision maker's choice for the i th criterion over j th criterion and the "tilde" denotes the triangular number (Buckley, 1985). As a result, Awang et al (2017) ) are averaged by aggregation of individual decision maker's judgment to conclude at a group consensus decision. In the AHP form, it is best to use geometric means since they are the only ones that keep the matrix reciprocal instead of arithmetic means (Aczel and Saaty, 1983;Krej and Stoklasa, 2018).…”

Developing a scale of social commerce service quality: an exploratory study

“…To calculate the consistency of each comparison matrix, the fuzzy numbers are converted into crisp numbers by defuzzification methods. In this study, each pairwise comparison matrix was defuzzified with Chang et al's (2009) method similar to the works of Chen et al (2017) and Awang et al (2017). In Chang et al's method, considering the preference (a) and risk tolerance (l ) of decision-makers, the decision-makers can understand the uncertainties they face under different circumstances.…”