An integrated and discriminative approach for group decision-making with probabilistic linguistic information
01 Feb 2021-Vol. 25, Iss: 4, pp 3043-3057
TL;DR: A prescriptive approach to GDM that can aid a group of decision-makers (DMs) to arrive at a decision is concerned, and the recent concept of probabilistic linguistic term set is utilized.
Abstract: Group decision-making (GDM) is a complex process. The diversity, discrimination, and inevitable uncertainty due to human intervention characterize such problems that add to this complexity. To circumvent this challenge, there is an urge for an appropriate knowledge representation and decision-making approaches. The present paper is concerned with a prescriptive approach to GDM that can aid a group of decision-makers (DMs) to arrive at a decision. To this end, the recent concept of probabilistic linguistic term set is utilized. The discrimination among the alternatives, as in the real world, are mimicked using an integrated framework that adopts CRITIC and variance methods for attribute weight calculation, Gini index for calculating the weights of DMs, Maclaurin symmetric mean for aggregating preferences, and weighted distance-based approximation for prioritization of alternatives. A real-world problem on electric bike selection illustrates the usefulness of the proposed work. Finally, comparative analysis with extant methods demonstrates the technical results, and it is inferred that the proposed work is (i) highly consistent (from Spearman correlation) and (ii) produces broad rank values (from standard deviation) that could be efficiently discriminated for rational decision-making and backup management during critical situations.
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TL;DR: The successful application of this new probabilistic linguistic TODIM method based on PT (PT-PL-TODIM method) in the selection of ICSSS proves that the model is practical and is also of great value to the decision-making research related to ICS.
Abstract: The close combination of internet technology and traditional industrial control system (ICS) is a double-edged sword, which not only improves the accuracy of the control system, but also brings great danger. According to the statistics of the authoritative industrial security incident information database, Repository of Industrial Security Incidents (RISI), as of October 2011, there have been more than 200 attacks on industrial control systems around the world. It is obviously a multi-attribute decision-making (MADM) problem to select the appropriate industrial control system security supplier (ICSSS) for ensuring the safety of ICS. In this paper, the traditional TODIM method is improved and reconstructed in the probabilistic linguistic environment by incorporating the prospect theory (PT) which has received close attention recently. In this new model, the entropy weight method is used to obtain the attribute weight under complete information. And based on the ideas of PT as well as traditional TODIM method, the distortion of decision results caused by the risk attitude and psychological state of decision makers is corrected as far as possible. In my opinion, probabilistic linguistic term set (PLTS) ensures that the model can better cope with the real environment and the complexity and ambiguity of decision makers’ thinking. Finally, the successful application of this new probabilistic linguistic TODIM method based on PT (PT-PL-TODIM method) in the selection of ICSSS proves that the model is practical and is also of great value to the decision-making research related to ICS. Moreover, the comparative analysis between the proposed model and the existing model effectively confirms the reliability of the proposed method. In the future, it is hoped that this method can be successfully applied to more decision-making fields.
53 citations
TL;DR: A novel integrated framework by combining criteria interaction through inter-criteria correlation (CRITIC) and multi-objective optimization based on ratio analysis with the full multiplicative form (MULTIMOORA) methods with single-valued neutrosophic sets (SVNSs) for assessing the multi-Criteria food waste treatment methods selection is offered.
Abstract: Proper management and treatment of food waste have become a key concern due to its significant environmental, social, and economic ramifications. The selection of the most appropriate food waste treatment method among a set of alternative methods can be regarded as a multi-criteria decision-making problem because of the association of numerous qualitative and quantitative attributes. In this paper, we offer a novel integrated framework by combining criteria interaction through inter-criteria correlation (CRITIC) and multi-objective optimization based on ratio analysis with the full multiplicative form (MULTIMOORA) methods with single-valued neutrosophic sets (SVNSs) for assessing the multi-criteria food waste treatment methods selection. In this methodology, the CRITIC technique is applied for computing the attribute weights, and the MULTIMOORA model is employed for estimating the ranking of the options within SVNSs context. To examine the introduced methodology’s efficiency and achievability, a case study of food waste treatment method (FWTM) assessment is discussed in the SVNSs setting. Further, comparative study and sensitivity investigation are offered to certify the presented framework for prioritizing FWTMs. The final results indicate that the proposed approach achieves better solutions than the extant models.
49 citations
TL;DR: An integrated decision making method based on the IG‐PLSHA operator is developed, taking DMs' risk attitudes into account, and an example is provided to illustrate the feasibility and practicality of the developed method.
Abstract: This paper investigates multiple attribute group decision making (MAGDM) with probabilistic linguistic term sets (PLTSs) and proposes an integrated decision method for solving such problems. First, a novel distance measure of PLTSs is defined, and then a distance‐based entropy measure and similarity measure are proposed. Subsequently, supposing that elements are independent of each other, an induced generalized PL‐ordered weighted average (IG‐PLOWA) operator and an induced generalized PL hybrid average (IG‐PLHA) operator are introduced. Afterwards, considering some cases in which elements are interactive, an induced generalized probabilistic linguistic Shapley hybrid average (IG‐PLSHA) operator is presented, and some desirable properties of this operator are further studied. Fusing the entropy and similarity degrees of decision makers (DMs), DM weights are determined objectively. Then, considering the interactions among attributes and the psychological behaviors of DMs, the models for obtaining the fuzzy measures on the attribute set are built based on the Shapley values and the prospect theory. Finally, taking DMs' risk attitudes into account, an integrated decision making method based on the IG‐PLSHA operator is developed. At length, an example is provided to illustrate the feasibility and practicality of the developed method.
7 citations
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TL;DR: The Analytic Hierarchy Process (AHP) is a theory of measurement through pairwise comparisons and relies on the judgements of experts to derive priority scales that measure intangibles in relative terms.
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TL;DR: The Analytic Hierarchy Process (AHP) as discussed by the authors is a theory of measurement through pairwise comparisons and relies on the judgements of experts to derive priority scales, these scales are these scales that measure intangibles in relative terms.
Abstract: Decisions involve many intangibles that need to be traded off. To do that, they have to be measured along side tangibles whose measurements must also be evaluated as to, how well, they serve the objectives of the decision maker. The Analytic Hierarchy Process (AHP) is a theory of measurement through pairwise comparisons and relies on the judgements of experts to derive priority scales. It is these scales that measure intangibles in relative terms. The comparisons are made using a scale of absolute judgements that represents, how much more, one element dominates another with respect to a given attribute. The judgements may be inconsistent, and how to measure inconsistency and improve the judgements, when possible to obtain better consistency is a concern of the AHP. The derived priority scales are synthesised by multiplying them by the priority of their parent nodes and adding for all such nodes. An illustration is included.
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