A state-of the-art survey & testbed of Fuzzy AHP (FAHP) applications

As a practical popular methodology for dealing with fuzziness and uncertainty in Multiple Criteria Decision-Making (MCDM), Fuzzy AHP (FAHP) has been applied to a wide range of applications. As of the time of writing there is no state of the art survey of FAHP, we carry out a literature review of 190 application papers (i.e., applied research papers), published between 2004 and 2016, by classifying them on the basis of the area of application, the identified theme, the year of publication, and so forth. The identified themes and application areas have been chosen based upon the latest state-of-the-art survey of AHP conducted by Vaidya and Kumar (2006). To help readers extract quick and meaningful information, the reviewed papers are summarized in various tabular formats and charts. Unlike previous literature surveys, results and findings are made available through an online (and free) testbed, which can serve as a ready reference for those who wish to apply, modify or extend FAHP in various applications areas. This online testbed makes also available one or more fuzzy pairwise comparison matrices (FPCMs) from all the reviewed papers (255 matrices in total). In terms of results and findings, this survey shows that: (i) FAHP is used primarily in the Manufacturing, Industry and Government sectors; (ii) Asia is the torchbearer in this field, where FAHP is mostly applied in the theme areas of Selection and Evaluation; (iii) a significant amount of research papers (43% of the reviewed literature) combine FAHP with other tools, particularly with TOPSIS, QFD and ANP (AHP’s variant); (iv) Chang’s extent analysis method, which is used for FPCMs’ weight derivation in FAHP, is still the most popular method in spite of a number of criticisms in recent years (considered in 57% of the reviewed literature)

A Systematic Review of Marine Risk Assessment: The Fuzzy Analytic Hierarchy Process (FAHP)

This systematic review examines the marine risk assessment (MRA) by identifying the most viable method in assessing marine risks using the latest technology. This paper centers on the Fuzzy Analytic Hierarchy Process (FAHP) where the techniques and advantages of FAHP in facilitating important decisions were analyzed. A systematic review of the literature was conducted to highlight the significance and potentials of FAHP in providing a comprehensive risk assessment analysis which serves as a standard applicable guideline in the marine industry. Firstly, a systematic search in three electronic databases (Mendeley, Scopus and ScienceDirect) was performed to collect relevant literature. They are database. Upon finalizing the data, a systematic review was conducted accordingly. Drawing from various disciplines of risk assessment, this paper presents the analysis and findings of several studies employing different analytical methods using FAHP. The results of this review offer further insights and alternatives concerning hierarchical decision-making especially in the field of risk assessment

Knowledge-based Consistency Index for Fuzzy Pairwise Comparison Matrices

Abstract—Fuzzy AHP is today one of the most used Multiple Criteria Decision-Making (MCDM) techniques. The main argument to introduce fuzzy set theory within AHP lies in its ability to handle uncertainty and vagueness arising from decision makers (when performing pairwise comparisons between a set of criteria/alternatives). As humans usually reason with granular information rather than precise one, such pairwise comparisons may contain some degree of inconsistency that needs to be properly tackled to guarantee the relevance of the result/ranking. Over the last decades, several consistency indexes designed for fuzzy pairwise comparison matrices (FPCMs) were proposed, as will be discussed in this article. However, for some decision theory specialists, it appears that most of these indexes fail to be properly “axiomatically” founded, thus leading to misleading results. To overcome this, a new index, referred to as KCI (Knowledge-based Consistency Index) is introduced in this paper, and later compared with an existing index that is axiomatically well founded. The comparison results show that (i) both indexes perform similarly from a consistency measurement perspective, but (ii) KCI contributes to significantly reduce the computation time, which can save expert’s time in some MCDM problems

A Systematic Review of Marine Risk Assessment: The Fuzzy Analytic Hierarchy Process (FAHP)

This systematic review examines the marine risk assessment (MRA) by identifying the most viable method in assessing marine risks using the latest technology. This paper centers on the Fuzzy Analytic Hierarchy Process (FAHP) where the techniques and advantages of FAHP in facilitating important decisions were analyzed. A systematic review of the literature was conducted to highlight the significance and potentials of FAHP in providing a comprehensive risk assessment analysis which serves as a standard applicable guideline in the marine industry. Firstly, a systematic search in three electronic databases (Mendeley, Scopus and ScienceDirect) was performed to collect relevant literature. They are database. Upon finalizing the data, a systematic review was conducted accordingly. Drawing from various disciplines of risk assessment, this paper presents the analysis and findings of several studies employing different analytical methods using FAHP. The results of this review offer further insights and alternatives concerning hierarchical decision-making especially in the field of risk assessment

Combining Fuzzy AHP with GIS and Decision Rules for Industrial Site Selection

This study combines Fuzzy Analytic Hierarchy Process (FAHP), Geographic Information System (GIS) and Decision rules to provide decision makers with a ranking model for industrial sites in Algeria. A ranking of the suitable industrial areas is a crucial multi-criteria decision problem based on socio-economical and technical criteria as on environmental considerations. Fuzzy AHP is used for assessment of the candidate industrial sites by combining fuzzy set theory and analytic hierarchy process (AHP). The decision rule base serves as a filter that performs criteria pre-treatment involving a reduction of their numbers. GIS is used to overlay, generate criteria maps and for visualizing ranked zones on the map. The rank of a zone so obtained is an index that guides decision-makers to the best utilization of the zone in future

Factors affecting energy consumption and productivity in greenhouses

Aim of study: To investigate the impact factors affecting the greenhouse environment on energy consumption and productivity.Area of study: Alborz province of Iran during the period 2018–2020.Material and methods: In this study, 18 active units of greenhouse owners in Alborz province of Iran that had necessary standards were identified. Then, upper and lower amplitudes of the variables affecting productivity and energy consumption in greenhouses were calculated using a type-2 fuzzy neural network, Matlab 2017 software. Area, temperature, energy exchange, environmental evapotranspiration and relative humidity were studied as indicators.Main results: With each unit of temperature, energy consumption and productivity increased by 0.737% and 0.741%, respectively; with each unit of energy exchange, they increased by 0.813% and 0.696%, respectively; with each unit of evaporation and transpiration of the environment, they increased by 0.593% and 0.869%, respectively; and with each unit of humidity, they increased by 0.398% and 0.509%, respectively.Research highlights: The factors affecting the greenhouse environment such as area, temperature, evapotranspiration and relative humidity had a significant effect on productivity in studying greenhouses and therefore increasing their productivity. According to the results, the model’s ability in energy consumption was better than that for energy efficiency prediction. Also, greenhouse ranking was done by FAHP method

A hybrid multicriteria approach to GPR image mining applied to water supply system maintenance

[EN] Data processing techniques for Ground Penetrating Radar (GPR) image mining provide essential information to optimize maintenance management of Water Supply Systems (WSSs). These techniques aim to elaborate on radargrams in order to produce meaningful graphical representations of critical buried components of WSSs. These representations are helpful non-destructive evaluation tools to prevent possible failures in WSSs by keeping them adequately monitored. This paper proposes an integrated multi-criteria decision making (MCDM) approach to prioritize various data processing techniques by means of ranking their outputs, namely their resulting GPR image representations. The Fuzzy Analytic Hierarchy Process (FAHP) is applied to weight various evaluation criteria, with the purpose of managing vagueness and uncertainty characterizing experts' judgments. Then, the Elimination Et Choix Traduisant la REalite III (ELECTRE III) method is used to obtain the final ranking of alternatives. A real case study, focusing on a set of four GPR images as outputs of different data processing techniques, is presented to prove the usefulness of the proposed hybrid approach. In particular, the GPR images are ranked according the evaluation of five criteria namely visualization, interpretation, identification of features, extraction of information and affordability. The findings offer a structured support in selecting the most suitable data processing technique(s) to explore WSS underground. In the presented case, two options, namely the variance filter and the subtraction methods, offer the best results. (C) 2018 Elsevier B.V. All rights reserved.Part of this work has been developed under the support of the Universitat Politecnica de Valencia, Valencia (Spain), grant: UPV mobility program for PhD students, awarded to the first author, and of Fundacion Carolina PhD, within its short stage scholarship program awarded to the second author.Carpitella, S.; Ocaña-Levario, SJ.; Benítez López, J.; Certa, A.; Izquierdo Sebastián, J. (2018). A hybrid multicriteria approach to GPR image mining applied to water supply system maintenance. Journal of Applied Geophysics. 159:754-764. https://doi.org/10.1016/j.jappgeo.2018.10.021S75476415

Knowledge-based Consistency Index for Fuzzy Pairwise Comparison Matrices

Abstract—Fuzzy AHP is today one of the most used Multiple Criteria Decision-Making (MCDM) techniques. The main argument to introduce fuzzy set theory within AHP lies in its ability to handle uncertainty and vagueness arising from decision makers (when performing pairwise comparisons between a set of criteria/alternatives). As humans usually reason with granular information rather than precise one, such pairwise comparisons may contain some degree of inconsistency that needs to be properly tackled to guarantee the relevance of the result/ranking. Over the last decades, several consistency indexes designed for fuzzy pairwise comparison matrices (FPCMs) were proposed, as will be discussed in this article. However, for some decision theory specialists, it appears that most of these indexes fail to be properly “axiomatically” founded, thus leading to misleading results. To overcome this, a new index, referred to as KCI (Knowledge-based Consistency Index) is introduced in this paper, and later compared with an existing index that is axiomatically well founded. The comparison results show that (i) both indexes perform similarly from a consistency measurement perspective, but (ii) KCI contributes to significantly reduce the computation time, which can save expert’s time in some MCDM problems

Three Decades of Fuzzy AHP: A Bibliometric Analysis

[EN] For decades, Fuzzy Sets Theory (FST) has been consistently developed, and its use has spread across multiple disciplines. In this process of knowledge transfer, fuzzy applications have experienced great diffusion. Among them, Fuzzy Analytic Hierarchy Process (fuzzy AHP) is one of the most widely used methodologies today. This study performs a systematic review following the PRISMA statement and addresses a bibliometric analysis of all articles published on fuzzy AHP in journals indexed in Web of Science, specifically in Science Citation Index Expanded (SCIE) and Social Science Citation Index (SSCI). The analyzed database includes 2086 articles published between 1994 and 2022. The results show the thematic clusters, the evolution of the academic conversation and the main collaboration networks. The main contribution of this article is to clarify the research agenda on fuzzy AHP. The results of the study allow academics to detect publication opportunities. In addition, the evidence found allows researchers and academics setting the field¿s agenda to advise the editors of high-impact journals on gaps and new research trends.Castello-Sirvent, F.; Meneses-Eraso, C.; Alonso-Gómez, J.; Peris-Ortiz, M. (2022). Three Decades of Fuzzy AHP: A Bibliometric Analysis. Axioms. 11(10):1-34. https://doi.org/10.3390/axioms11100525134111