Sustainable food waste management using modified fuzzy improved analytic hierarchy process: A case study in Malaysia - Choo, Chun Yuan (2023)
Sustaining food waste generation is a problem that must be addressed to avoid negative impacts on the environment, society, and economy, which can be achieved by choosing a good food waste management method. One suitable method to evaluate the alternatives of sustainable food waste management within multi-criteria decision making is Improved Analytical Hierarchy Process (IAHP). The IAHP can handle consistency issues while considering various criteria and alternatives. However, it is lacking in the aspect of data transformations and uncertain judgment of the decision-makers. Thus, this study aims to develop a Modified Fuzzy IAHP to determine the most sustainable food waste management in Malaysia. The method is developed through the integration of (i) IAHP to determine the weight of criteria, sub-criteria, and alternatives of food waste management, (ii) linear max and sum normalization methods to transform data into numerical and comparable data with standardized beneficial and non-beneficial criteria, (iii) geometric mean method to handle the uncertainty involved in human judgments, and (iv) centroid method to convert fuzzy weight into the crisp set which ease for interpretation. There were four criteria, 21 sub-criteria, and four alternatives considered in the case study. The findings of this paper show that environmental is the most important criterion followed by social, economic, and technical. Furthermore, air and water pollution is found to be the most important sub-criterion. Black Soldier Fly is discovered as the most sustainable food waste management alternative since it performed the best while meeting all the criteria and sub-criteria assessed. Sensitivity analysis demonstrated that the outputs from the proposed method were consistent and reliable. This study can provide a modified method for tackling conflict criteria and alternatives, which assists decision makers in selecting suitable food waste management.