An Enhanced Technique for Order Preference by Similarity to Ideal Solutions and its Application to Renewable Energy Resources Selection Problem

Abstract

Selecting right renewable energy resources (RESs) is emerging as a solution to alleviate energy crisis and environmental pollution. To better address the RESs selection problems, this paper proposes an enhanced Technique for Order Preference by Similarity to Ideal Solutions (TOPSIS). Specifically, the decision information is characterized by linguistic terms and then encoded by interval type-2 fuzzy sets (IT2FSs). The current IT2FSs preprocessing models recklessly transform IT2FSs into crisp numbers, which may discount the superiority of applying fuzzy sets. Hence, we define a novel interval type-2 fuzzy projection model to measure the IT2FSs and some related theorems about the projection model are explored mathematically. Moreover, based on this new interval type-2 fuzzy projection model, an enhanced TOPSIS is proposed to calculate the closeness coefficients of alternatives. Of note, to keep information as much as possible, the obtained closeness coefficients are still IT2FSs. Finally, the Karnik–Mendel (KM) algorithms are employed to compare and rank those closeness coefficients. The effectiveness of the proposed method is demonstrated by a RESs selection case. Comparisons are also conducted to illustrate its advantages.