Sustainability assessment and decision making of hydrogen production technologies: A novel two-stage multi-criteria decision making method. (4th December 2020)

• Record Type: Journal Article
• Authors: Ren, Xusheng; Li, Weichen; Ding, Shimin; Dong, Lichun
• Is Part Of: International journal of hydrogen energy. Volume 45:Number 59(2020)
• Page Start: 34371
• Page End: 34384
• Publication Date: 2020-12-04
• Subjects: Hydrogen production technology -- Fuzzy TOPSIS -- Fuzzy best-worst method -- Two-stage multi-criteria decision-making -- Preference information on alternatives; Hydrogen as fuel -- Periodicals; Hydrogène (Combustible) -- Périodiques; Hydrogen as fuel; Periodicals; 665.81
• DOI: 10.1016/j.ijhydene.2019.12.134
• Languages: English
• ISSNs: 0360-3199

Abstract

Abstract: A novel two-stage multi-criteria decision making (MCDM) method is proposed with the aim to select the most sustainable hydrogen production technology (HPT) by considering the preference information on both attributes and alternatives. In the first stage of the method, the initial sustainability ranking of the alternative HPTs was achieved by using the FBWM (Fuzzy Best-Worst Method) to determine the weights of the criteria and the fuzzy TOPSIS (Technique for Order Performance by Similarity to Ideal Solution) method to prioritize the sustainability of alternative HPTs. While, in the second stage, a novel Preference Ranking Linear Programming Method (PRLPM) was used to acquire the final sustainability ranking according to the alternative preference information by following the principle of the outranking method. The proposed method was illustrated by a case study with 8 HTPs, demonstrating that the developed two-stage MCDM method can reflect the alternative preference of the decision-maker more accurately for selecting the most preferred alternative among various HTPs. Highlights: The MCDM framework divides the sustainability decision-making into two stages. Fuzzy best-worst method and fuzzy TOPSIS were used in the first stage. A novel method based on preference information on alternatives is proposed. The framework combines preference information on attributes and alternatives.