Elsevier

Expert Systems with Applications

Volume 65, 15 December 2016, Pages 398-422
Expert Systems with Applications

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

https://doi.org/10.1016/j.eswa.2016.08.064Get rights and content

Highlights

  • A state-of the-art survey of FAHP applications is carried out: 190 papers are reviewed

  • Papers are classified based on their: Application area, Theme, Year, Country, etc.

  • Review is summarized in tabular formats/charts to help readers extract quick info.

  • Results and Findings are made available through an online (free) testbed

  • The testbed makes fuzzy pairwise comparison matrices (from all papers) available

Abstract

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, O., & Kumar, S. (2006). Analytic hierarchy process: An overview of applications. European Journal of operational research, 169(1), 1–29.]. 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).

Introduction

Multiple criteria decision-making (MCDM) methods are frequently used to solve real world problems with multiple, conflicting, and incommensurate criteria and/or objectives. Hwang and Yoon (1981) have classified the MCDM methods into two categories: multi-attribute decision-making (MADM) and multi-objective decision-making (MODM). MADM techniques, unlike MODM, heavily involves human participation and judgments. Research on human judgments and decision making shows that the human brain is able to consider only a limited amount of information at any one time (Simpson, 1996), which makes it unreliable to take decisions when facing complex problems. Analytic Hierarchy Process (AHP), initially introduced by Saaty (1980), is by now one of the most widely applied MADM techniques, whose main strength lies in its impartial and logical grading system (reducing personal biases and allowing for comparing dissimilar alternatives), but also in its flexibility to be integrated with various techniques like Linear Programming, Quality Function Deployment, Fuzzy Logic, etc. (Saaty, Vargas, 2001, Vaidya, Kumar, 2006). This enables users to extract benefits from all the combined methods and achieve the desired goal in a better way.

As a practical popular methodology for dealing with fuzziness and uncertainty, the Fuzzy Logic combined with AHP, more commonly known as Fuzzy AHP or FAHP (van Laarhoven & Pedrycz, 1983), has found huge applications in recent years. According to a recent survey on Fuzzy MCDM techniques (Mardani, Jusoh, & Zavadskas, 2015), FAHP is the second most widely used technique in a stand-alone mode (just after AHP). Since, as of this writing, no state-of-the-art survey of FAHP has been issued – the latest survey being dedicated to AHP and dating back to 2006 (Vaidya & Kumar, 2006) – this article looks into the research papers with a view to understand the spread of FAHP in different fields. Based on a classification scheme, a reference repository has been established, including around 200 international journal papers (starting from 2004). Papers have been classified based on various dimension s, including the year of publication, application area, identified theme, authors’ nationality, etc. This survey goes along with an online and free testbed1 that makes the results and findings of this study available, as well as one or more fuzzy pairwise comparison matrices (FPCMs) from all reviewed papers. For the anecdote, the genesis of this state-of-the-art survey started from a personal motivation around the study and development of new consistency indexes for FPCMs’ weight derivation, which is still a sensitive issue in the FAHP literature. In this context, we started the collection of FPCMs from scientific articles, which has led to the achievement of this survey. We believe that this online testbed will serve as a ready reference for those who wish to apply, modify or extend FAHP in various application domains, including scientists (e.g., for benchmarking purposes), reviewers and journal editors (e.g., to evaluate the relevance of future research papers), and other categories of practitioners.

The proposed state-of the-art survey is structured as follows: Section 2 discusses to what extent MADM techniques are important to overcome complex real-life problems involving different categories of stakeholders, in various sectors. Section 2 also discusses in greater detail how FAHP stands with regard to existing MCDM techniques, and what are the basic principles underlying (F)AHP. Section 3 details the research methodology considered to collect, classify and analyze the journal papers. Section 4 provides the breakdown of the literature review. Section 5 offers a comprehensive summary of the survey outcomes, graphical representations, and concluding remarks. Section 6 presents the online FAHP/FPCMs testbed; conclusion and research directions follow.

Section snippets

Background

Section 2.1 discusses why MADM techniques are widely applied to various sectors today, along with a general overview of how FAHP stands with regard to existing MCDM techniques. Following this introduction, the theories/principles underlying AHP and FAHP are respectively presented in Sections 2.2 and 2.3.

Research methodology

In our study, we collected articles that have been published in popular scientific journals and provided the most important information to practitioners and researchers who investigate FAHP-related issues. To this end, an extensive search was carried out to find FAHP2 in titles, abstracts, keywords, and research methodologies of the papers. Our study attempts to document the high interest in FAHP, and provides a

Survey results

The structure of this section is built based on the chosen “Themes”, i.e. all reviewed papers that make use of FAHP for Selection purposes are presented in Section 4.1, for Evaluation purposes in Section 4.2, and so on. In each of these sections, papers are summarized in tabular formats considering the following dimensions: Application area, Other tool(s) used, Year and Specific objective (specific to the problem addressed in each paper). A unique identifier is also attributed to each paper in

Observations and concluding remarks

In an effort to provide a clear and comprehensive summary of the survey outcomes, Sections 5.1 to 5.6 present graphical and tabular representations, syntheses and discussions of the FAHP method as a developed decision making tool. Whenever possible, the survey outcomes are compared with findings and predictions from past MCDM-related surveys such as (Vaidya & Kumar, 2006) (AHP-related survey), (Mardani et al., 2015) (Fuzzy MCDM-related survey) and (Behzadian, Khanmohammadi Otaghsara, Yazdani, &

Open FAHP/FPCMs testbed

As it has been explained in the introduction section, this state-of-the-art survey started from a personal motivation around the study of a new consistency index for FPCMs’ weight derivation, for which we started the collection of FPCMs from various scientific journal papers with the objective to use them as basis of a testbed to evaluate the proposed consistency index. This gave us the idea to make all those FPCMs’ available online (for free) to various communities of researchers. In total,

State-of the-art survey’s conclusion

Because human decision-making contains fuzziness and vagueness, FAHP is often applied to tackle MCDM problems. Although a number of criticisms have been levelled against FAHP, or more specifically against scientific methods used to derive weights from fuzzy pairwise comparison matrices (FPCMs), FAHP remains very popular. Its popularity is due to its flexibility to be combined with other techniques (e.g., TOPSIS, QFD, LP...) and its simplicity of implementation. Given the high number of

Acknowlegement

The research leading to this publication is supported by the National Research Fund Luxembourg under grant agreement n° 9095399, as well as the European Union’s H2020 Programme for research, technological development and demonstration under grant agreement n° 688203.

References (232)

  • E. Bulut et al.

    Rotational priority investigation in fuzzy analytic hierarchy process design: An empirical study on the marine engine selection problem

    Applied Mathematical Modelling

    (2015)
  • G. Büyüközkan et al.

    Strategic analysis of healthcare service quality using fuzzy ahp methodology

    Expert Systems with Applications

    (2011)
  • G. Büyüközkan et al.

    A combined fuzzy ahp and fuzzy topsis based strategic analysis of electronic service quality in healthcare industry

    Expert Systems with Applications

    (2012)
  • G. Büyüközkan et al.

    A new approach based on soft computing to accelerate the selection of new product ideas

    Computers in Industry

    (2004)
  • G. Büyüközkan et al.

    Fuzzy group decision-making to multiple preference formats in quality function deployment

    Computers in Industry

    (2007)
  • A. Calabrese et al.

    Using fuzzy ahp to manage intellectual capital assets: An application to the ict service industry

    Expert Systems with Applications

    (2013)
  • M.C. Carnero

    Multicriteria model for maintenance benchmarking

    Journal of Manufacturing Systems

    (2014)
  • U. Cebeci

    Fuzzy ahp-based decision support system for selecting erp systems in textile industry by using balanced scorecard

    Expert Systems with Applications

    (2009)
  • M. Celik et al.

    Application of fuzzy extended ahp methodology on shipping registry selection: The case of turkish maritime industry

    Expert Systems with Applications

    (2009)
  • D.-Y. Chang

    Applications of the extent analysis method on fuzzy ahp

    European Journal of Operational Research

    (1996)
  • S.-C. Chang et al.

    The features and marketability of certificates for occupational safety and health management in taiwan

    Safety Science

    (2016)
  • S.-C. Chang et al.

    A hybrid fuzzy model for selecting and evaluating the e-book business model: A case study on taiwan e-book firms

    Applied Soft Computing

    (2015)
  • J.-F. Chen et al.

    Evaluating teaching performance based on fuzzy ahp and comprehensive evaluation approach

    Applied Soft Computing

    (2015)
  • L.-H. Chen et al.

    An evaluation approach to logistics service using fuzzy theory, quality function development and goal programming

    Computers & Industrial Engineering

    (2006)
  • S. Chen et al.

    Fuzzy risk analysis based on the ranking of generalized trapezoidal fuzzy numbers

    Applied Intelligence

    (2007)
  • D.W. Cho et al.

    A framework for measuring the performance of service supply chain management

    Computers & Industrial Engineering

    (2012)
  • J. Cho et al.

    Development of a new technology product evaluation model for assessing commercialization opportunities using delphi method and fuzzy ahp approach

    Expert Systems with Applications

    (2013)
  • J.-S. Chou et al.

    Bidding strategy to support decision-making by integrating fuzzy ahp and regression-based simulation

    Automation in Construction

    (2013)
  • Y.-C. Chou et al.

    Evaluating the criteria for human resource for science and technology (hrst) based on an integrated fuzzy ahp and fuzzy dematel approach

    Applied Soft Computing

    (2012)
  • D. Choudhary et al.

    An steep-fuzzy ahp-topsis framework for evaluation and selection of thermal power plant location: A case study from india

    Energy

    (2012)
  • M.M.H. Chowdhury et al.

    A multi-phased qfd based optimization approach to sustainable service design

    International Journal of Production Economics

    (2016)
  • R. Csutora et al.

    Fuzzy hierarchical analysis: The lambda-max method

    Fuzzy sets and Systems

    (2001)
  • M.C. Das et al.

    A Framework to measure relative performance of indian technical institutions using integrated fuzzy ahp and copras methodology

    Socio-Economic Planning Sciences

    (2012)
  • Y. Deng et al.

    Biogas as a sustainable energy source in china: Regional development strategy application and decision making

    Renewable & Sustainable Energy Reviews

    (2014)
  • D. Dubois

    The role of fuzzy sets in decision sciences: Old techniques and new directions

    Fuzzy Sets and Systems

    (2011)
  • O. Durán

    Computer-aided maintenance management systems selection based on a fuzzy ahp approach

    Advances in Engineering Software

    (2011)
  • O. Durán et al.

    Computer-aided machine-tool selection based on a fuzzy-ahp approach

    Expert Systems with Applications

    (2008)
  • O. Duru et al.

    Regime switching fuzzy ahp model for choice-varying priorities problem and expert consistency prioritization: A cubic fuzzy-priority matrix design

    Expert Systems with Applications

    (2012)
  • B. Efe

    An integrated fuzzy multi criteria group decision making approach for erp system selection

    Applied Soft Computing

    (2016)
  • İ. Ertuğrul et al.

    Performance evaluation of turkish cement firms with fuzzy analytic hierarchy process and topsis methods

    Expert Systems with Applications

    (2009)
  • M. Golestanifar et al.

    A multi-dimensional approach to the assessment of tunnel excavation methods

    International Journal of Rock Mechanics and Mining Sciences

    (2011)
  • K. Govindan et al.

    Analyzing the drivers of green manufacturing with fuzzy approach

    Journal of Cleaner Production

    (2015)
  • A.T. Gumus

    Evaluation of hazardous waste transportation firms by using a two step fuzzy-ahp and topsis methodology

    Expert Systems with Applications

    (2009)
  • D.R. Insua et al.

    A framework for sensitivity analysis in discrete multi-objective decision-making

    European Journal of Operational Research

    (1991)
  • M.T. Isaai et al.

    Intelligent timetable evaluation using fuzzy ahp

    Expert systems with Applications

    (2011)
  • A. Ishizaka et al.

    Calibrated fuzzy ahp for current bank account selection

    Expert Systems with Applications

    (2013)
  • P. Jakiel et al.

    Fahp model used for assessment of highway rc bridge structural and technological arrangements

    Expert Systems with Applications

    (2015)
  • M.B. Javanbarg et al.

    Fuzzy ahp-based multicriteria decision making systems using particle swarm optimization

    Expert Systems with Applications

    (2012)
  • Y. Ju et al.

    Evaluating emergency response capacity by fuzzy ahp and 2-tuple fuzzy linguistic approach

    Expert Systems with Applications

    (2012)
  • M. Kabak et al.

    A fuzzy multi-criteria decision making approach to assess building energy performance

    Energy and Buildings

    (2014)
  • Cited by (356)

    View all citing articles on Scopus
    View full text