A new scaling MCDA procedure putting together pairwise comparison tables and the deck of cards method

This paper deals with an improved version of the deck of the cards method to render the construction of the ratio and interval scales more `accurate'. The improvement comes from the fact that we can account for a richer and finer preference information provided by the decision-makers, which permits a more accurate modelling of the strength of preference between two consecutive levels of a scale. Instead of considering only the number of blank cards between consecutive positions in the ranking of objects such as criteria and scale levels, we consider also the number of blank cards between non consecutive positions in the ranking. This information is collected in a pairwise comparison table that it is not necessarily built with precise values. We can consider also missing information and imprecise information provided in the form of ranges. Since the information provided by the decision-makers is not necessarily consistent, we propose also some procedures to help the decision-maker to make consistent his evaluations in a co-constructive way interacting with an analyst and reflecting and revising her/his judgments. The method is illustrated through and example in which, generalizing the SWING method, interacting criteria are aggregated through the Choquet integral.

[1]  Tommi Tervonen,et al.  Notes on 'Hit-And-Run enables efficient weight generation for simulation-based multiple criteria decision analysis' , 2014, Eur. J. Oper. Res..

[2]  P. Wakker Additive Representations of Preferences: A New Foundation of Decision Analysis , 1988 .

[3]  R. L. Keeney,et al.  Decisions with Multiple Objectives: Preferences and Value Trade-Offs , 1977, IEEE Transactions on Systems, Man, and Cybernetics.

[4]  Robert L. Smith,et al.  Efficient Monte Carlo Procedures for Generating Points Uniformly Distributed over Bounded Regions , 1984, Oper. Res..

[5]  Ki Hang Kim Measurement theory with applications to decision-making, utility and the social sciences: Fred S. Robert Reading, MA 01867: Addison-Wesley, 1979. $24.50 , 1981 .

[6]  Bernard Roy,et al.  Determining the weights of criteria in the ELECTRE type methods with a revised Simos' procedure , 2002, Eur. J. Oper. Res..

[7]  Salvatore Greco,et al.  Robust Ranking of Universities Evaluated by Hierarchical and Interacting Criteria , 2018, Multiple Criteria Decision Making and Aiding.

[8]  Risto Lahdelma,et al.  SMAA - Stochastic multiobjective acceptability analysis , 1998, Eur. J. Oper. Res..

[9]  G. Rota On the foundations of combinatorial theory I. Theory of Möbius Functions , 1964 .

[10]  Eleftherios Siskos,et al.  Elicitation of criteria importance weights through the Simos method: A robustness concern , 2015, Eur. J. Oper. Res..

[11]  W. Edwards,et al.  Decision Analysis and Behavioral Research , 1986 .

[12]  C. B. E. Costa,et al.  MACBETH — An Interactive Path Towards the Construction of Cardinal Value Functions , 1994 .

[13]  Salvatore Greco,et al.  Non-additive robust ordinal regression: A multiple criteria decision model based on the Choquet integral , 2010, Eur. J. Oper. Res..

[14]  S. Greco,et al.  A robust ranking method extending ELECTRE III to hierarchy of interacting criteria, imprecise weights and stochastic analysis , 2017 .

[15]  G. Rota On the Foundations of Combinatorial Theory , 2009 .

[16]  Valentina Ferretti,et al.  A Choquet integral-based approach for assessing the sustainability of a new waste incinerator , 2013 .

[17]  J. Figueira,et al.  A survey on stochastic multicriteria acceptability analysis methods , 2008 .

[18]  Salvatore Greco,et al.  Multiple Criteria Hierarchy Process for ELECTRE Tri methods , 2016, Eur. J. Oper. Res..

[19]  Renata Pelissari,et al.  SMAA methods and their applications: a literature review and future research directions , 2020, Ann. Oper. Res..

[20]  T. L. Saaty A Scaling Method for Priorities in Hierarchical Structures , 1977 .

[21]  Salvatore Greco,et al.  Ordinal regression revisited: Multiple criteria ranking using a set of additive value functions , 2008, Eur. J. Oper. Res..

[22]  M. Grabisch The application of fuzzy integrals in multicriteria decision making , 1996 .

[23]  J. Siskos Assessing a set of additive utility functions for multicriteria decision-making , 1982 .

[24]  Matthias Ehrgott,et al.  Multiple criteria decision analysis: state of the art surveys , 2005 .

[25]  Michel Grabisch,et al.  K-order Additive Discrete Fuzzy Measures and Their Representation , 1997, Fuzzy Sets Syst..

[26]  Salvatore Greco,et al.  An Overview of ELECTRE Methods and their Recent Extensions , 2013 .

[27]  Jacques Pictet,et al.  Extended use of the cards procedure as a simple elicitation technique for MAVT. Application to public procurement in Switzerland , 2008, Eur. J. Oper. Res..

[28]  Ralph L. Keeney,et al.  Decisions with multiple objectives: preferences and value tradeoffs , 1976 .

[29]  Tommi Tervonen,et al.  Hit-And-Run enables efficient weight generation for simulation-based multiple criteria decision analysis , 2013, Eur. J. Oper. Res..

[30]  G. Choquet Theory of capacities , 1954 .

[31]  José Rui Figueira,et al.  On the Choquet multiple criteria preference aggregation model: Theoretical and practical insights from a real-world application , 2018, Eur. J. Oper. Res..

[32]  Michel Grabisch,et al.  A decade of application of the Choquet and Sugeno integrals in multi-criteria decision aid , 2010, Ann. Oper. Res..

[33]  Lucien Yves Maystre,et al.  Méthodes multicritères ELECTRE : description, conseils pratiques et cas d'application à la gestion environnementale , 1994 .