BENCHMARKING FUZZY-BASED MCDM APPROACHES IN RENEWABLE ENERGY SOURCES SELECTION: A NEW INTERVAL-VALUED NEUTROSOPHIC FUZZY DEMATEL-ANP-TOPSIS FRAMEWORK


Çelikbilek Y.

Eurasian Econometrics, Statistics & Empirical Economics Journal, cilt.26, ss.138-168, 2025 (Hakemli Dergi)

Özet

Assessing  renewable  energy resources  requires  robust  multi-criteria  decision-making  tools  capable  of  handling uncertainty, vagueness, and the complex interactions among sustainability-related criteria. This study provides a comprehensive comparison of several widely used fuzzy-basedmulti-criteria decision-making methods applied to renewable  energy  source  evaluation,  including  Fuzzy  DEMATEL,  Fuzzy  AHP,  Fuzzy  ANP,  Fuzzy  TOPSIS, Fuzzy VIKOR, Fuzzy COPRAS, Fuzzy ELECTRE, etc., and also spherical, intuitionistic or neutrosophic fuzzy variants  reported  in  the  literature.  By  applying  each  method  to  the  same  dataset,  the  analysis  highlights  the similarities,  divergences,  and  sensitivity  patterns  that  emerge  across  different  fuzzy  modelling  perspectives. Building on these  comparative  insights,  the  study introduces a  novel  interval-valued neutrosophic  fuzzy  hybrid decision-making framework integrating DEMATEL, ANP, and TOPSIS. In the proposed model, interval-valued neutrosophic fuzzy DEMATEL is employed to capture causal relationships among criteria and determine influence weights,  while interval-valued neutrosophic fuzzy  ANP  models interdependencies  within the  decision  network. Finally,  interval-valued  neutrosophic  fuzzy  TOPSIS  is  used  to  generate  a  robust  and  discriminative  ranking  of renewable  energy  source  alternatives.  The  results  demonstrate  that  the  hybrid  interval-valued  neutrosophic framework offers enhanced consistency, stronger representation of expert hesitation, and improved prioritization stability  compared  with  conventional  fuzzy  MCDM  methods.  Overall,  this  study  advances  the  methodological landscape  of  renewable  energy  source  decision-making  by  both  benchmarking  existing  fuzzy  techniques  and proposing  an  innovative  interval-valued  neutrosophic  hybrid  approach  that  can  support  more reliable  and sustainable energy planning.