A review of multiple criteria sorting methods: bibliometrics, characteristics, applications and prospects

Abstract

Multiple criteria sorting (MCS) refers to assigning alternatives to ordered classes based on the evaluation values of alternatives on multiple criteria. Researchers have developed various methods to solve MCS problems. There is a need to sort out the research in this area to enable researchers to understand the current state of research and the challenges in terms of methods and applications. Different from existing review papers on MCS methods, this paper explores the research progress of MCS methods and summarises characteristics and limitations of existing MCS methods. The research status, key areas of focus, and emerging trends in this field are outlined through bibliometric analysis. Characteristics of different MCS methods from the perspectives of value/utility functions, outranking relations, and decision-rules are analysed and then the applications of MCS methods are summarised. Finally, lessons learned from the review and future research directions are discussed.

KEYWORDS:

• Multiple criteria sorting
• value function
• outranking
• decision-rule
• review
• bibliometrics

Acknowledgements

The authors deeply appreciate associate editor for his encouragement and patience. We also express our gratitude to the anonymous referees for their valuable comments and constructive suggestions that improve the quality of the paper.

Disclosure statement

The authors have no competing financial, professional, or personal interests from other parties that are related to this paper.

Notes

1 The reference profile of each class consists of either a central profile or limiting profile(s): when classes are characterized by limiting profiles, the profiles can be denoted as $l{p}_1,\cdots ,l{p}_s,\cdots ,l{p}_{k-1}$), where the class $G_s$ is defined by its lower-limit profile $l{p}_s$ and upper-limit profile $l{p}_{s+1}$; when classes are defined by central profiles, the profiles are denoted by $c{p}_1,\cdots ,c{p}_s,\cdots ,c{p}_{k-1}$, where $c{p}_s$ is the central of the class $G_s$.

2 Web of Science. https://www.webofscience.com/wos/woscc/basic-search

3 VOSviewer stands as a bibliometric analysis tool renowned for its robust visualization capabilities, and it is conveniently accessible via: http://www.vosviewer.com/.

4 Synonymous keywords are combined to reduce redundancy, such as ‘mcda’ and ‘mcdm’. Necessary simplifications are performed to save space for the screen shot like Figure 3, such as using abbreviations or replacing ‘rough set approach’ by ‘rough sets’.

Additional information

Funding

The work was supported by the National Natural Science Foundation of China (Nos. 72371173, 72171158, 71971145), and the Fundamental Research Funds for the Central Universities (No. SCU2022CG02, No. 2023ZY-SX001).

Notes on contributors

Huchang Liao

Huchang Liao received his PhD degree in Management Science and Engineering from the Shanghai Jiao Tong University, Shanghai, China in 2015. He is currently a Research Fellow at the Business School, Sichuan University, Chengdu, China. He has published more than 350 peer reviewed papers, many in high-quality international journals. His publications have been cited over 19,000 times in Google Scholar, and his h-index is 77. His current research interests include multiple criteria decision analysis and fuzzy set and systems. He has been a Highly Cited Researcher (2019–2023). Prof. Liao has been elected to be the Fellow of IFSA, IET, BCS, and RSA. He is the Area Editor of International Journal of Information Technology & Decision Making, Associate Editor, Guest Editor or Editorial Board Member for many top-tier international journals such as IEEE Transactions on Fuzzy Systems and Journal of Control and Decision.

Yue Xiao

Yue Xiao is a Ph.D. candidate majoring in Management Science and Engineering from the Business School, Sichuan University, Chengdu, China. She has published several papers in international journals such as Information Sciences, International Journal of Intelligent Systems. At present, her main research direction is decision analysis, evidential reasoning under uncertainty environment.

Zheng Wu

Zheng Wu is a Ph.D. candidate majoring in Management Science and Engineering from the Business School, Sichuan University, Chengdu, China. He has published several papers in international journals, including Information Sciences, Engineering Applications of Artificial Intelligence, International Journal of Intelligent Systems, and Journal of the Operational Research Society. His current research interests include group decision making, energy transition, and social network analysis.

Zhi Wen

Zhi Wen is a Ph.D. candidate majoring in Management Science and Engineering from the Business School, Sichuan University, Chengdu, China. She has published several papers in international journals such as Annals of Operations Research, Information Processing & Management, and Operations Management Research. At present, her main research direction is multiple criteria sorting methods under uncertainty.