Abstract
This paper puts forward the use of data visualization in a new method for solving multiple criteria decision-making problems for ranking of alternatives, based on Flexible and Interactive Tradeoff (FITradeoff) elicitation. This approach uses partial information about the decision maker’s preferences, based on a structured process for eliciting scale constants (or weights) within the scope of multi-attribute value theory. Different from most of the partial information methods present in the literature, our approach is based on the traditional Tradeoff, which is the most axiomatically founded procedure for elicitation of criteria weights. Pairwise dominance concept is incorporated into the mathematical model of FITradeoff in such way that, at each interaction with the decision maker, a partial—or complete—order of the alternatives can be achieved, based on a two-step algorithm proposed. The method is operated by means of a decision support system, which provides graphical visualization of the ranking at each interaction, in order to support the decision-making process with a simpler visualization of dominance relations. The proposed method is applied for solving a practical case of supplier selection in a food industry.
Similar content being viewed by others
References
Ahn BS, Park KS (2008) Comparing methods for multiattribute decision making with ordinal weights. Comput Oper Res 35(5):1660–1670
Athanassopoulos AD, Podinovski VV (1997) Dominance and potential optimality in multiple criteria decision analysis with imprecise information. J Oper Res Soc 48(2):142–150
Barron FH, Barrett BE (1996) Decision quality using ranked attribute weights. Manage Sci 42(11):1515–1523
Belton V, Stewart T (2002) Multiple criteria decision analysis: an integrated approach. Springer, Berlin
Borcherding K, Eppel T, Von Winterfeldt D (1991) Comparison of weighting judgments in multiattribute utility measurement. Manage Sci 37(12):1603–1619
Ciomek K, Kadziński M, Tervonen T (2017) Heuristics for selecting pair-wise elicitation questions in multiple criteria choice problems. Eur J Oper Res 262(2):693–707
Danielson M, Ekenberg L, He Y (2014) Augmenting ordinal methods of attribute weight approximation. Decis Anal 11(1):21–26
De Almeida AT, Roselli LRP (2017) Visualization for decision support in FITradeoff method: exploring its evaluation with cognitive neuroscience. In: Linden I, Liu C, Colot C (eds) Decision Support Systems VII. Data, Information and Knowledge Visualization in Decision Support Systems. LNBIP, vol 282., pp 1–13. https://doi.org/10.1007/978-3-319-57487-5_5
De Almeida AT, Almeida JA, Costa APCS, Almeida-Filho AT (2016) A new method for elicitation of criteria weights in additive models: flexible and interactive tradeoff. Eur J Oper Res 250(1):179–191
Dell’Ovo M, Frej EA, Oppio A, Capolongo S, Morais DC, De Almeida AT (2017) Multicriteria decision making for healthcare facilities location with visualization based on FITradeoff method. In: Linden I, Liu S, Colot C (eds) Decision Support Systems VII. Data, Information and Knowledge Visualization in Decision Support Systems. LNBIP, vol 282., pp 32–44. https://doi.org/10.1007/978-3-319-57487-5_3
Edwards W, Barron FH (1994) SMARTS and SMARTER: improved simple methods for multiattribute utility measurement. Organ Behav Hum Decis Process 60(3):306–325
Gusmão APH, Medeiros CP (2016) A model for selecting a strategic information system using the FITradeoff. Math Probl Eng. ID 7850960
Keeney RL, Raiffa H (1976) Decision analysis with multiple conflicting objectives. Wiley, New York
Kirkwood CW, Sarin RK (1985) Ranking with partial information: a method and an application. Oper Res 33(1):38–48
López JCL, Carrillo PAÁ, Chavira DAG, Noriega JJS (2017) A web-based group decision support system for multicriteria ranking problems. Oper Res Int J 17(2):499–534
Malakooti B (2000) Ranking and screening multiple criteria alternatives with partial information and use of ordinal and cardinal strength of preferences. IEEE Trans Syst Man Cybern Part A Syst Hum 30(3):355–368
Mármol AM, Puerto J, Fernández FR (2002) Sequential incorporation of imprecise information in multiple criteria decision processes. Eur J Oper Res 137(1):123–133
Montiel LV, Bickel JE (2014) A generalized sampling approach for multilinear utility functions given partial preference information. Decis Anal 11(3):147–170
Mustajoki J, Hämäläinen RP, Salo A (2005) Decision support by interval SMART/SWING—incorporating imprecision in the SMART and SWING methods. Decis Sci 36(2):317–339
Park K (2004) Mathematical programming models for characterizing dominance and potential optimality when multicriteria alternative values and weights are simultaneously incomplete. IEEE Trans Syst Man Cybern Part a: Syst Hum 34(5):601–614
Park KS, Kim SH (1997) Tools for interactive multiattribute decision-making with incompletely identified information. Eur J Oper Res 98(1):111–123
Park KS, Lee KS, Eum YS, Park K (2001) Extended methods for identifying dominance and potential optimality in multi-criteria analysis with imprecise information. Eur J Oper Res 134(3):557–563
Salo AA, Hamalainen RP (2001) Preference ratios in multiattribute evaluation (PRIME)-elicitation and decision procedures under incomplete information. IEEE Trans Syst Man Cybern Part A: Syst Hum 31(6):533–545
Salo AA, Hämäläinen RP (1992) Preference assessment by imprecise ratio statements. Oper Res 40(6):1053–1061
Salo A, Punkka A (2005) Rank inclusion in criteria hierarchies. Eur J Oper Res 163(2):338–356
Sarabando P, Dias LC (2010) Simple procedures of choice in multicriteria problems without precise information about the alternatives’ values. Comput Oper Res 37(12):2239–2247
Stillwell WG, Seaver DA, Edwards W (1981) A comparison of weight approximation techniques in multiattribute utility decision making. Organ Behav Hum Perform 28(1):62–77
Weber M (1987) Decision making with incomplete information. Eur J Oper Res 28(1):44–57
Weber M, Borcherding K (1993) Behavioral influences on weight judgments in multiattribute decision making. Eur J Oper Res 67(1):1–12
Acknowledgements
The authors would like to acknowledge CNPq for the partial financial support for this research.
Funding
This work was supported by the National Council for Scientific and Technological Development (CNPq).
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that they have no conflict of interest.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Frej, E.A., de Almeida, A.T. & Costa, A.P.C.S. Using data visualization for ranking alternatives with partial information and interactive tradeoff elicitation. Oper Res Int J 19, 909–931 (2019). https://doi.org/10.1007/s12351-018-00444-2
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12351-018-00444-2