Fuzzified Analytical Planning for Climate Mitigation Policy Formulation

Li Lun

Abstract

This research investigates the climate mitigation policy formulation method with the incorporation of fuzzy numbers with the aim of choosing the best climate mitigation policy for Singapore. The literature review explores the existing climate mitigation policies and their respective effectiveness in various countries around the world. It also investigates in the different methods for climate mitigation policy formulation. The AHP decomposes complex decision making problems into sub-problems by using a tree structure. The relative importance of criteria and alternatives is determined using a method of pair-wise comparison. However, this method is based on the assumption that humans are very good at making pair-wise comparisons and capable of expressing the comparisons by crisp numbers. In reality, human behavior is not as simple as this. A model is developed to take the fuzziness of human behavior in decision making into account. More specifically, an integrated assessment approach, incorporated with forward and backward analytical planning and triangular fuzzy numbers, is used to choose the best climate mitigation policy. The results indicate that Carbon tax policy may be the policy should be adopted by Singapore in consideration of the multiple criteria identified by the author.