Fuzzy Weighted Zero Inconsistency Method (FWZIC) for Multi-Criteria Decision-Making Weighting Criteria: A Systematic Literature Review

Abstract

 Researchers in various fields have consistently used Multi-Criteria Decision-Making (MCDM)
methods for discipline improvement, employing both standard and novel approaches. Selecting a weighting
mechanism for evaluation criteria is critical in MCDM problems. Recognizing the importance of remaining up to
date on such developments in methodology, this study aims to review several innovative methods integrated with
Fuzzy Weighted Zero Inconsistency (FWZIC). Relying on the papers taken from the significant databases: IEEE
Xplore (IEEE), ScienceDirect (SD), Scopus, and PubMed from 23 August 2023 to 30 October 2023, where each
method was read and analyzed for its characteristics and steps. These indexes were deemaed extensive and
dependable enough to encompass the scope of our literature review. A total number of articles, n = 26 were chosen
based on the criteria for inclusion and exclusion have been selected for this systematic review. By using
bibliometric and content analysis, this study examined the developing ways with (FWZIC), as well as study
components (sources, authors, different countries, and affiliations), areas of application, case studies, fuzzy
implementations, hybrid studies (use of other weighting methods), and application tools for these methods. The
results of this literature systematic review (LSR) provide an accurate depiction of each new development related to
the weighting method and its utilization, such as: 1- Extracting the types of development employed in the FWZIC
approach based on Fuzzy Set. 2- Extracting types of aggregation operators. 3- Analyzing integration methods with
FWZIC (hybridized with other methods), and 4- Case study types showing how MCDM approaches may help
decision-makers in a variety of decisions. Also, a set of recommendations has been presented to the researchers for
the development of new method types, as a new direction for future work. This will provide academics and
practitioners in the field of MCDM with valuable insights and significant expertise for data analysis and decisionmaking.