Comprehensive evaluation of sustainable ammonia production systems based on fuzzy multiattribute decision making under hybrid information

Abstract

The comprehensive evaluation of ammonia production systems is of great significance for improving the sustainability of energy management and food supply. Therefore, an important contribution could be provided by developing a generic decision-making framework for prioritizing multiple ammonia production systems and identifying the best one. In this view, this paper aims to propose an integrated fuzzy MADM (multiattribute decision making) framework combining fuzzy BWM (best-worst method), fuzzy CRITIC (Criteria Importance Through Intercriteria Correlation), and fuzzy GRP (gray relational projection) approaches for the sustainability assessment of ammonia production systems under hybrid information. Comparing with the previous MADM-based frameworks for sustainability assessment, this framework adopts the TFN (triangular fuzzy number) to deal with the hybrid information (ie, crisp numbers, interval values, and fuzzy numbers) that arise from real-world decision-making issues. Accordingly, the weights of criteria can be comprehensively determined by integrating the fuzzy BWM and fuzzy CRITIC, which balance experts' subjective preferences and system's objective properties under uncertainties in the determination of the weights, while the sequence of alternatives can be reliably prioritized by extending the GRP into fuzzy conditions, which escalates the ranking capability under hybrid information via considering the relationships and relative balance among the alternatives' performances regarding the multicriteria. Seven alternative systems were studied by the proposed framework, indicating that ammonia generated from hydropower-electrolysis and coal gasification would be more preferable than the others, by considering 12 criteria from the concerns of technological, environmental, economic, and social-political. Additionally, sensitivity analysis and result comparison were conducted to verify the rationality and feasibility of the framework. This work makes a methodological contribution to the MADM-based sustainability research and serves as a reference for developing the ammonia economy in the future. K E Y W O R D Sammonia production system, combined weights, fuzzy best-worst method, fuzzy gray relational projection, hybrid information, sustainability assessment

An extended MABAC method based on prospect theory with unknown weight information under Fermatean fuzzy environment for risk investment assessment in B&R

“…For the hybrid assessment issue, Xu et al. ( 2020 ) built up a comprehensive assessment model based on BWM, CRITIC approach and Gray relation analysis to address evaluation issues with hybrid information. Lai and Liao ( 2021 ) propounded a MCDM decision method through synthesizing the DNMA and CRITIC methods under linguistic D number to select an optimal blockchain platform.…”

A 2-dimensional uncertain linguistic MABAC method for multiattribute group decision-making problems

“…A smaller value of CR(close to zero) indicates higher consistency of the pairwise comparisons, whereas a larger value of CR(close to one) indicates inferior consistency [51]. If CR ≥ 0.1 , the comparisons have to be adjusted [39].…”

A Hybrid Multi-Attribute Decision-Making Approach Considering Correlations Among Indicators

“…Different types of information are usually transformed into the same type of information to facilitate the ranking before obtaining the final ranking result. Reference [6] used triangular fuzzy numbers to deal with the mixed decision-making information generated by realistic decision-making problems, and improved the ranking ability under mixed information by considering the relationship and relative balance between alternative performances under multiple criteria. Reference [7] proposed a new method for solving mixed multi-attribute decision problems with multiple attribute values by introducing the decision maker's closeness to the positive ideal solution and the eclectic variable-weight decision-making method.…”