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Analysis of rank reversal problems in “Weighted Aggregated Sum Product Assessment” method

  • Soft computing in decision making and in modeling in economics
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Abstract

Multiple attribute decision-making (MADM) methods are commonly employed to assist decisions for selecting the best alternative according to conflicting criteria in complex decision situations. Although MADM methods have proven to be very useful, in some dynamic decision cases they may cause faulty results due to the “rank reversals” problem. Numerous MADM methods such as Analytic Hierarchy Process (AHP), Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE), and several others well-known methods proven to have rank reversal problems. In this paper, we study the rank reversal problem for a recent MADM method that is known as Weighted Aggregated Sum Product Assessment (WASPAS). As far as we know, there is no study that considers the rank reversal problem in the WASPAS. In this paper, rank reversal problems in WASPAS are analyzed empirically by considering different types of rank reversals. After detailed computational experiments, we show that rank reversal problems also exist in WASPAS when classical normalization techniques are utilized. We also show through extensive computational experiments by using different problem instances that rank reversal problems can be avoided in WASPAS when modified Max and Max–Min normalization techniques are used.

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References

  • Anbaroglu B, Heydecker B, Cheng T (2014) Spatio-temporal clustering for nonrecurrent traffic congestion detection on urban road networks. Transp Res Part C: Emerg Technol 48:47–65

    Article  Google Scholar 

  • Antucheviciene J, Zakarevicius A, Zavadskas EK (2011) Measuring Congruence of ranking results applying particular MCDM methods. Informatica 22(3):319–338

    Article  MathSciNet  MATH  Google Scholar 

  • Bagočius V, Zavadskas EK, Turskis Z (2014) Multi-person selection of the best wind turbine based on the multi-criteria integrated additive-multiplicative utility function. J Civ Eng Manag 20:590–599

    Article  Google Scholar 

  • Baykasoğlu A, Gölcük İ (2019) Revisiting ranking accuracy within WASPAS method. Kybernetes 49(3):885–895

    Article  Google Scholar 

  • Belton V, Gear T (1983) On a short-coming of Saaty’s method of analytic hierarchies. Omega 11(3):228–230

    Article  Google Scholar 

  • Buede DM, Maxwell DT (1995) Rank disagreement: A comparison of multi-criteria methodologies. J Multi-Criteria Decis Anal 4(1):1–21

    Article  MATH  Google Scholar 

  • Ceballos B, Pelta DA, Lamata MT (2018) Rank reversal and the VIKOR method: an empirical evaluation. Int J Inf Technol Decis Mak 17(2):513–525

    Article  Google Scholar 

  • Chakraborty S, Zavadskas EK (2014) Applications of WASPAS method in manufacturing decision making. Informatica 25(1):1–20

    Article  Google Scholar 

  • Chakraborty S, Zavadskas EK, Antucheviciene J (2015) Applications of WASPAS method as a multi-criteria decision-making tool. Econ Comput Econ Cybern Stud Res 49(1):5–22

    Google Scholar 

  • Cinelli M, Coles SR, Kirwan K (2014) Analysis of the potentials of multi criteria decision analysis methods to conduct sustainability assessment. Ecol Ind 46:138–148

    Article  Google Scholar 

  • de Farias Aires RF, Ferreira L (2018) The rank reversal problem in multi-criteria decision-making: a literature review. Pesquisa Operacional 38(2):1–32

    Google Scholar 

  • de Farias Aires RF, Ferreira L (2019) A new approach to avoid rank reversal cases in the TOPSIS method. Comput Ind Eng 132:1–14

    Google Scholar 

  • Dejus T, Antucheviciene J (2013) Assessment of health and safety solutions at a construction site. J Civ Eng Manag 19:728–737

    Article  Google Scholar 

  • Finan JS, Hurley WJ (2002) The analytic hierarchy process: can wash criteria be ignored? Comput Oper Res 29(8):1025–1030

    Article  MATH  Google Scholar 

  • García-Cascales MS, Lamata MT (2012) On rank reversal and TOPSIS method. Math Comput Model 56(5–6):123–132

    Article  MathSciNet  MATH  Google Scholar 

  • Hashemkhani Zolfani S, Aghdaie MH, Derakhti A, Zavadskas EK, Varzandeh MHM (2013) Decision making on business issues with foresight perspective;an application of new hybrid MCDM model in shopping mall locating. Expert Syst Appl 40:7111–7121

    Article  Google Scholar 

  • Huszák A, Imre S (2010) Eliminating rank reversal phenomenon in GRA-based network selection method. In: 2010 IEEE International Conference on Communications, pp. 1–6

  • Jahan A (2018) Developing WASPAS-RTB method for range target-based criteria: toward selection for robust design. Technol Econ Dev Econ 24(4):1362–1387

    Article  Google Scholar 

  • Jain, N., Singh A.R., & Choudhary, A.K. (2016). Integrated methodology for supplier selection in supply chain management. In: 2016 IEEE International conference on industrial engineering and engineering management (IEEM), Bali, pp. 807–811

  • Jan KH, Tung C-T, Deng P (2011) Rank reversal problem related to wash criterion in analytic hierarchy process (AHP). Afr J Bus Manage 5(20):8301–8306

    Google Scholar 

  • Jung S-T, Wou Y-W, Li S-P, Julian P (2009) A revisit to wash criteria in analytic hierarchy process. Far East J Math Sci 34(1):31–36

    MATH  Google Scholar 

  • Kong F (2011) Rank reversal and rank preservation in TOPSIS. Adv Mater Res 204–210:36–41

    Article  Google Scholar 

  • Lin JSJ, Chou SY, Chouhuang WT, Hsu CP (2008) Note on “wash criterion in analytic hierarchy process.” Eur J Oper Res 185(1):444–447

    Article  MATH  Google Scholar 

  • Liu X, Ma Y (2021) A method to analyze the rank reversal problem in the ELECTRE II method. Omega 102:102317

    Article  Google Scholar 

  • Madić M, Radovanović M, Petković D, Nedić B (2015) Selection of cutting inserts for aluminum alloys machining by using MCDM method. ACTA Universitatis Cibiniensis 66(1):98–101

    Article  Google Scholar 

  • Majumdar A, Tiwari MK, Agarwal A, Prajapat K (2021) A new case of rank reversal in analytic hierarchy process due to aggregation of cost and benefit criteria. Op Res Perspect 8:100185

    MathSciNet  Google Scholar 

  • Maleki H, Zahir S (2013) A comprehensive literature review of the rank reversal phenomenon in the analytic hierarchy process. J Multi-Criteria Decis Anal 20(3–4):141–155

    Article  Google Scholar 

  • Mardani A, Nilashi M, Zakuan N, Loganathan N, Soheilirad S, Saman MZM, Ibrahim O (2017) A systematic review and meta-analysis of SWARA and WASPAS methods: theory and applications with recent fuzzy developments. Appl Soft Comput 57:265–292

    Article  Google Scholar 

  • Mousavi-Nasab SH, Sotoudeh-Anvari A (2018) A new multi-criteria decision making approach for sustainable material selection problem: a critical study on rank reversal problem. J Clean Prod 182:464–484

    Article  Google Scholar 

  • Nezhad MRG, Hashemkhani Zolfani S, Moztarzadeh F, Zavadskas EK, Bahrami M (2015) Planning the priority of high tech industries based on SWARA-WASPAS methodology: the case of the nanotechnology industry in Iran. Econ Res-Ekonomska Istraživanja 28(1):1111–1137

    Article  Google Scholar 

  • Ramanathan U, Ramanathan R (2011) An investigation into rank reversal properties of the multiplicative AHP. Int J Op Res 11(1):54–77

    Article  Google Scholar 

  • Saaty TL (1980) The analytic hierarchy process. McGraw Hill, New York

    MATH  Google Scholar 

  • Saaty TL, Vargas LG (1984a) Inconsistency and rank preservation. J Math Psychol 28(2):205–214

    Article  MathSciNet  MATH  Google Scholar 

  • Saaty TL, Vargas LG (1984b) The legitimacy of rank reversal. Omega 12(5):513–516

    Article  Google Scholar 

  • Simanaviciene R, Ustinovicius L (2012) A new approach to assessing the biases of decisions based on multiple attribute decision making methods. Elektronika Ir Elektrotechnika 117(1):29–32

    Article  Google Scholar 

  • Tang H, Fang F (2018) A novel improvement on rank reversal in TOPSIS based on the efficacy coefficient method. Int J Internet Manuf Serv 5(1):67–84

    Google Scholar 

  • Tiwari RK, Kumar R (2021) G-TOPSIS: a cloud service selection framework using Gaussian TOPSIS for rank reversal problem. J Supercomput 77:523–562

    Article  Google Scholar 

  • Triantaphyllou E, Shu B (2001) On the maximum number of feasible ranking sequences in multi-criteria decision-making problems. Eur J Oper Res 130(3):665–678

    Article  MathSciNet  MATH  Google Scholar 

  • Turskis Z, Zavadskas EK, Antucheviciene J, Kosareva N (2015) A hybrid model based on fuzzy AHP and fuzzy WASPAS for construction site selection. Int J Comput Commun Control 10:113–128

    Article  Google Scholar 

  • Verly C, De Smet Y (2013) Some results about rank reversal instances in the PROMETHEE methods. Int J Multicrit Decis Making 3(4):325–345

    Article  Google Scholar 

  • Wang YM, Luo Y (2009) On rank reversal in decision analysis. Math Comput Model 49(5–6):1221–1229

    Article  MathSciNet  MATH  Google Scholar 

  • Wang X, Triantaphyllou E (2008) Ranking irregularities when evaluating alternatives by using some ELECTRE methods. Omega 36(1):45–63

    Article  Google Scholar 

  • Yang W (2020) Ingenious solution for the rank reversal problem of TOPSIS method. Math Probl Eng 2020:9676518

    MathSciNet  Google Scholar 

  • Yang W, Wu Y (2020) A new improvement method to avoid rank reversal in VIKOR. IEEE Access 8:21261–21271

    Article  Google Scholar 

  • Yücenur GN, Ipekçi A (2021) SWARA/WASPAS methods for a marine current energy plant location selection problem. Renew Energy 163:1287–1298

    Article  Google Scholar 

  • Zahir S (2009) Normalisation and rank reversals in the additive analytic hierarchy process: a new analysis. Int J Op Res 4(4):446–467

    Article  MATH  Google Scholar 

  • Zanakis SH, Solomon A, Wishart N, Dublish S (1998) Multi-attribute decision making: a simulation comparison of select methods. Eur J Oper Res 107(3):507–529

    Article  MATH  Google Scholar 

  • Zavadskas EK, Zakarevicius A, Antucheviciene J (2006) Evaluation of ranking accuracy in multi-criteria decisions. Informatica 17(4):601–618

    Article  MathSciNet  MATH  Google Scholar 

  • Zavadskas EK, Turskis Z, Antucheviciene J, Zakarevicius A (2012) Optimization of weighted aggregated sum product assessment. Elektronika Ir Elektrotechnika 122:3–6

    Article  Google Scholar 

  • Zhou M, Liu X-B, Qian X-F, Yang J-B, Wu J (2020) Assignment of attribute weights with belief distributions for MADM under uncertainties. Knowledge-Based Syst 189:105110

    Article  Google Scholar 

Download references

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AB Conceptualization; Methodology; Formal analysis and Investigation; Writing–original draft preparation; Writing–review and editing; Resources; Supervision. EE Conceptualization; Methodology; Formal analysis and Investigation; Writing–original draft preparation; Writing–review and editing.

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Correspondence to Adil Baykasoğlu.

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Baykasoğlu, A., Ercan, E. Analysis of rank reversal problems in “Weighted Aggregated Sum Product Assessment” method. Soft Comput 25, 15243–15254 (2021). https://doi.org/10.1007/s00500-021-06405-w

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