An extended Combined Compromise Solution technique based on novel intuitionistic fuzzy distance measure and score function with application to biomass waste management

Abstract

Nowadays, due to population growth and high living standards, the demand for energy resources is increasing. Biomass waste is an important source of energy generating. Selection of a suitable biomass waste management system relative to different factors is a complex decision making process. An extension of fuzzy sets, intuitionistic fuzzy (IF) sets are used to manage uncertainty in more complicated scenarios. In order to address the issue of choosing an appropriate biomass waste management system in light several criteria, this research presents a modified Combined Compromise Solution (CoCoSo) framework in an IF environment. For this, a new IF distance measure (IFDM) is proposed and establish its superiority in finding the pattern similarity of unknown patterns through some numerical examples. A novel score function that overcomes the shortcomings of the existing score functions is provided in order to address the comparison issue of IF numbers. The proposed framework is constructed by utilizing weighted sum and weighted product matrices. A new integration function in this framework is given which follows the double normalization process. Criteria weights and compromise rating scales are determined in this framework using the suggested distance measure and score function, respectively.