Sustainable food waste management using modified fuzzy improved analytic hierarchy process: a study of Malaysia

Food waste generation is a pressing issue that requires urgent attention and concerted efforts worldwide. The staggering amount of food wasted each year not only wastes valuable resources but also exacerbates environmental, economic, and social challenges. Food Waste Management (FWM) consists of a complex array of criteria and sub-criteria, and treatments which seems interdependent. There is a need to evaluate the FWM with the help of important criteria and sub-criteria and treatments to address this challenge. In this study, we identified four important criteria, 21 sub-criteria, and four alternatives of FWM for the case of Malaysia using the integrated approach of literature review and expert opinions. Further, we employed the approach of Modified Fuzzy Improved Analytical Hierarchy Process (IAHP) to corroborate the interrelationships among the identified criteria and sub-criteria, and their associated treatments. This study undertakes linear normalization methods to transform data into comparable numerical values and the Geometric Mean method to handle uncertainty in human judgments. Moreover, the Centroid method is employed to convert fuzzy weights into crisp sets for ease of interpretation. The results indicate that environmental is the most essential criterion, followed by social, economic, and technical. In addition, air and water pollution is identified as the most critical sub-criteria. Black Soldier Fly is discovered as the most sustainable FWM treatment, since it performs the best while meeting all the criteria and sub-criteria assessed. Sensitivity analysis demonstrates that the outputs from the proposed method are robust and reliable. The finding suggests a proper and robust approach to help decision-makers select suitable FWM treatments to tackle various criteria and alternatives especially when handling inconsistent and uncertain judgments during evaluation.