A Group Decision Framework for Renewable Energy Source Selection under Interval-Valued Probabilistic linguistic Term Set

Abstract

In recent years, the assessment of desirable renewable energy alternative has been an extremely important concern that could change the environment and economic growth. To tackle the circumstances, some authors have paid attention to selecting the desirable renewable energy option by employing the decision-making assessment and linguistic term sets. With a fast-growing interest in multi-criteria group decision-making (MCGDM) problems, researchers are tirelessly working towards new techniques for better decision-making. Decision makers (DMs) generally rate alternatives linguistically with different probabilities occurring for each term. Previous studies on linguistic decision-making have either ignored this idea or have used an only a single value for representing the weight of the linguistic term. Since expression of the complete probability distribution is hard and implicit hesitation exists, representation of weights of the linguistic terms using a single value becomes imprecise and unreasonable. To avoid this challenge, an interval-valued probabilistic linguistic term set (IVPLTS) is used, which is a generalization of (probabilistic linguistic term set) PLTS. Inspired by the usefulness of IVPLTS concept, we develop a decision framework for rational decision making. Initially, some operational laws and axioms are presented. Further, a novel aggregation operator known as interval-valued probabilistic linguistic simple weighted geometry (IVPLSWG) is developed for aggregating DMs’ preferences. Also, criteria weights are determined using the newly developed interval-valued probabilistic linguistic standard variance (IVPLSV) approach and alternatives are ranked using the extended VIKOR (VlseKriterijumskaOptimizacijaKompromisnoResenje) method under IVPLTS environment. Finally, a numerical example of renewable energy assessment is demonstrated to show the practicality of the developed decision framework. Also, the strengths and weaknesses of the developed decision framework are illustrated by comparison with existing ones.

Assessment of Energy Systems Using Extended Fuzzy AHP, Fuzzy VIKOR, and TOPSIS Approaches to Manage Non-Cooperative Opinions

“…They labeled MADM and fuzzy MADM approaches into the following groupings: AHP, VIKOR, TOPSIS, PROMETHEE, fuzzy sets, and system and ANP are mostly used for impact analysis, energy technology evaluation, and for the selection of the best place for energy generation. Krishankumar et al [33] discussed the framework of ranking the alternatives utilizing the developed interval-valued probabilistic linguistic term set (IVPLTS)-based classical VIKOR approach. Alizadeh et al [34] combined two models-Benefit, Opportunity, Cost, Risk, and ANP models-to determine the solar energy as the preferential renewable energy source for Iran.…”

A Novel IVPLTS Decision Method Based on Regret Theory and Cobweb Area Model

“…To further verify our method, IVPLTS-based VIKOR proposed by [11] is taken for comparison with our method. e main decision process of the method can be concluded as the following decision steps:…”

“…In this section, we will compare our method with the TOPSIS method for IVPLTS proposed by [10] and the VIKOR method proposed by [11].…”

“…Jin et al [10] proposed the basic operation rules and aggregation operators of uncertain probabilistic linguistic term set (UPLTS) and extended the traditional TOPSIS method to the UPLTS environment. Krishankumar et al [11] proposed interval-valued probabilistic linguistic simple weighted geometry (IVPLSWG) to aggregate preference information of decision makers and extended the VIKOR method to the decision environment of IVPLTS.…”

Z‐uncertain probabilistic linguistic variables and its application in emergency decision making for treatment of COVID‐19 patients

“…31 Studies on the probabilistic linguistic preference relations (PLPRs) [32][33][34][35][36][37] also emerged. Due to the advantages of simultaneously representing linguistic evaluation and preference information, PLTSs 20,[38][39][40][41][42] and its extended sets [43][44][45][46][47][48] were widely used in GDM.…”