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Theorem Verification of the Quantifier-Guided Dominance Degree with the Mean Operator for Additive Preference Relations. MATHEMATICS 2022. [DOI: 10.3390/math10122035] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Deciding which film is the best or which portfolio is the best for investment are examples of decisions made by people every day. Decision-making systems aim to help people make such choices. In general, a decision-making system processes and analyses the available information to arrive at the best alternative solution of the problem of interest. In the preference modelling framework, decision-making systems select the best alternative(s) by maximising a score or choice function defined by the decision makers’ expressed preferences on the set of feasible alternatives. Nevertheless, decision-making systems may have logical errors that cannot be appreciated by developers. The main contribution of this paper is the provision of a verification theorem of the score function based on the quantifier-guided dominance degree (QGDD) with the mean operator in the context of additive preference relations. The provided theorem has several benefits because it can be applied to verify that the result obtained is correct and that there are no problems in the programming of the corresponding decision-making systems, thus improving their reliability. Moreover, this theorem acts on different parts of such systems, since not only does the theorem verify that the order of alternatives is correct, but it also verifies that the creation of the global preference relation is correct.
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Hassani H, Razavi-Far R, Saif M, Herrera-Viedma E. Consensus-Based Decision Support Model and Fusion Architecture for Dynamic Decision Making. Inf Sci (N Y) 2022. [DOI: 10.1016/j.ins.2022.03.040] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
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Three-way group consensus decision based on hierarchical social network consisting of decision makers and participants. Inf Sci (N Y) 2022. [DOI: 10.1016/j.ins.2021.11.057] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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Hua Z, Xue H. A Maximum Consensus Improvement Method for Group Decision Making Under Social Network with Probabilistic Linguistic Information. Neural Process Lett 2021. [DOI: 10.1007/s11063-021-10639-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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