Eliminating Rank Reversal Problem Using a New Multi-Attribute Model—The RAFSI Method

Mališa Žižović, Dragan Pamučar, Miloljub Albijanić, Prasenjit Chatterjee and Ivan Pribićević
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Mališa Žižović: Faculty of Technical Sciences in Čačak, University of Kragujevac, Svetog Save 65, 32102 Čačak, Serbia
Dragan Pamučar: Department of Logistics, Military academy, University of Defence in Belgrade, Pavla Jurišića Šturma 33, 11000 Belgrade, Serbia
Miloljub Albijanić: Faculty of Economics, Finance and Administration, Metropolitan University, 11000 Belgrade, Serbia
Prasenjit Chatterjee: Department of Mechanical Engineering, MCKV Institute of Engineering, West Bengal, Howrah 711204, India
Ivan Pribićević: Simplify Outsourcing d.o.o. Belgrade, 11000 Belgrade, Serbia

Mathematics, 2020, vol. 8, issue 6, 1-16

Abstract: Multi-attribute decision-making (MADM) methods represent reliable ways to solve real-world problems for various applications by providing rational and logical solutions. In reaching such a goal, it is expected that MADM methods would eliminate inconsistencies like rank reversal issues in a given solution. In this paper, an endeavor is taken to put forward a new MADM method, called RAFSI (Ranking of Alternatives through Functional mapping of criterion sub-intervals into a Single Interval), which successfully eliminates the rank reversal problem. The developed RAFSI method has three major advantages that recommend it for further use: (i) its simple algorithm helps in solving complex real-world problems, (ii) RAFSI method has a new approach for data normalization, which transfers data from the starting decision-making matrix into any interval, suitable for making rational decisions, (iii) mathematical formulation of RAFSI method eliminates the rank reversal problem, which is one of the most significant shortcomings of existing MADM methods. A real-time case study that shows the advantages of RAFSI method is presented. Additional comprehensive analysis, including a comparison with other three traditional MADM methods that use different ways for data normalization and testing the resistance of RAFSI method and other MADM methods to rank the reversal problem, is also carried out.

Keywords: multi-criteria optimization; RAFSI method; performance comparison; rank reversal (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

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