An extension on PROMETHEE based on the typical hesitant fuzzy sets to solve multi-attribute decision-making problem

Kybernetes ◽  
2016 ◽  
Vol 45 (8) ◽  
pp. 1213-1231 ◽  
Author(s):  
Amin Mahmoudi ◽  
Soheil Sadi-Nezhad ◽  
Ahmad Makui ◽  
Mohammad Reza Vakili
Keyword(s):  
Decision Making ◽  
Decision Makers ◽  
Distance Functions ◽  
Fuzzy Information ◽  
Content Type ◽  
Decision Making Problem ◽  
Promethee Method ◽  
Multi Attribute Decision Making ◽  
Fuzzy Linguistic ◽  
Practical Implications

Purpose The purpose of this paper is to extend the PROMETHEE method under typical hesitant fuzzy information for solving multi-attribute decision-making problem in which there is hesitancy among experts. Design/methodology/approach Different aggregation and distance functions were developed to deal with HFS. But it is rational that different operators applying in existing methods can produce different results. Also, it is difficult for decision makers to select suitable operators. To address the drawback, this paper develops the PROMETHEE method as an outranking approach to accommodate hesitant fuzzy information. Since the proposed method is constructed on the basis of the pair-wise comparisons, it is independent of the aggregation and distance functions. Findings To demonstrate the efficiency and accuracy of the proposed method, the authors provide a numerical example and a comparative analysis. The results indicate that outranking-based methods suggest a better ranking than the aggregation- and distance-based methods. Research limitations/implications The proposed approach does not consider the hesitant fuzzy linguistic information decision-making problem. Practical implications The proposed approach can be applied in many group decision-making problems in which there is hesitancy among experts. Originality/value This paper proposes an extension on PROMETHEE method under hesitant fuzzy information, which has not been reported in the existing academic literature.

Who’s making the decisions? How managers can harness artificial intelligence and remain in charge

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Pooya Tabesh
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Decision Making ◽  
Big Data ◽  
Digital Transformation ◽  
Decision Processes ◽  
Decision Makers ◽  
Content Type ◽  
Human Decision ◽  
Practical Implications

Purpose While it is evident that the introduction of machine learning and the availability of big data have revolutionized various organizational operations and processes, existing academic and practitioner research within decision process literature has mostly ignored the nuances of these influences on human decision-making. Building on existing research in this area, this paper aims to define these concepts from a decision-making perspective and elaborates on the influences of these emerging technologies on human analytical and intuitive decision-making processes. Design/methodology/approach The authors first provide a holistic understanding of important drivers of digital transformation. The authors then conceptualize the impact that analytics tools built on artificial intelligence (AI) and big data have on intuitive and analytical human decision processes in organizations. Findings The authors discuss similarities and differences between machine learning and two human decision processes, namely, analysis and intuition. While it is difficult to jump to any conclusions about the future of machine learning, human decision-makers seem to continue to monopolize the majority of intuitive decision tasks, which will help them keep the upper hand (vis-à-vis machines), at least in the near future. Research limitations/implications The work contributes to research on rational (analytical) and intuitive processes of decision-making at the individual, group and organization levels by theorizing about the way these processes are influenced by advanced AI algorithms such as machine learning. Practical implications Decisions are building blocks of organizational success. Therefore, a better understanding of the way human decision processes can be impacted by advanced technologies will prepare managers to better use these technologies and make better decisions. By clarifying the boundaries/overlaps among concepts such as AI, machine learning and big data, the authors contribute to their successful adoption by business practitioners. Social implications The work suggests that human decision-makers will not be replaced by machines if they continue to invest in what they do best: critical thinking, intuitive analysis and creative problem-solving. Originality/value The work elaborates on important drivers of digital transformation from a decision-making perspective and discusses their practical implications for managers.

scholarly journals A Multi-Attribute Decision-Making Algorithm Using Q-Rung Orthopair Power Bonferroni Mean Operator and Its Application

Mathematics ◽  
2020 ◽  
Vol 8 (8) ◽  
pp. 1240 ◽  
Author(s):  
Ping He ◽  
Zaoli Yang ◽  
Bowen Hou
Keyword(s):  
Decision Making ◽  
Influence Factors ◽  
Uncertain Information ◽  
Fuzzy Information ◽  
Bonferroni Mean ◽  
Decision Making Problem ◽  
Multi Attribute Decision Making ◽  
New Type ◽  
Multiple Variables ◽  
Internal Relationship

The process of decision-making is subject to various influence factors and environmental uncertainties, which makes decision become a very complex task. As a new type of decision processing tool, the q-rung orthopair fuzzy sets can effectively deal with complex uncertain information arising in the decision process. To this end, this study proposes a new multi-attribute decision-making algorithm based on the power Bonferroni mean operator in the context of q-rung orthopair fuzzy information. In this method, in view of multi-attribute decision-making problem of internal relationship between multiple variables and extreme evaluation value, the Bonferroni mean operator is combined with power average operator. Then, the integrated operator is introduced into the q-rung orthopair fuzzy set to develop a new q-rung orthopair power Bonferroni mean operator, and some relevant properties of this new operator are discussed. Secondly, a multi-attribute decision-making method is established based on this proposed operator. Finally, the feasibility and superiority of our method are testified via a numerical example of investment partner selection in the tourism market.

scholarly journals A Method of Determining Multi-Attribute Weights Based on Single-Valued Neutrosophic Numbers and Its Application in TODIM

Symmetry ◽  
2019 ◽  
Vol 11 (4) ◽  
pp. 506 ◽  
Author(s):  
Dongsheng Xu ◽  
Yanran Hong ◽  
Kaili Xiang
Keyword(s):  
Decision Making ◽  
Decision Makers ◽  
Entropy Weight ◽  
Attribute Weights ◽  
Attribute Weight ◽  
Decision Making Problem ◽  
Entropy Weight Method ◽  
Todim Method ◽  
Multi Attribute Decision Making ◽  
Weight Method

In this paper, the TODIM method is used to solve the multi-attribute decision-making problem with unknown attribute weight in venture capital, and the decision information is given in the form of single-valued neutrosophic numbers. In order to consider the objectivity and subjectivity of decision-making problems reasonably, the optimal weight is obtained by combining subjective weights and objective weights. Subjective weights are given directly by decision makers. Objective weights are obtained by establishing a weight optimization model with known decision information, then this method will compare with entropy weight method. These simulation results also validate the effectiveness and reasonableness of this proposed method.

Multi-attribute Group Decision-making (MAGDM) using Fuzzy Linguistic Modeling Integrated with the VIKOR Method for Car Purchasing Model

2022 ◽  
Vol 14 (1) ◽  
pp. 0-0
Keyword(s):  
Decision Making ◽  
Group Decision ◽  
Decision Makers ◽  
Decision Making Process ◽  
Vikor Method ◽  
Decision Making Problem ◽  
Purchasing Model ◽  
The Individual ◽  
Fuzzy Linguistic

The change in the trend of transportation, increasing per capita income, expectation of better lifestyle, easy finance, and reduced cost of the automobile are some of the main factors that enable a commoner to have his/her own car. Therefore, it is essential to comprise such features in cars that offer qualities enabling the ease of consumer’s decision-making and comfort to purchase a car individually. Purchasing a car is a complicated multi-criteria decision-making problem as an individual may have different preferences for different criteria attributes. The attributes may be conflicting in nature depending on the need of the individual customer. Generally, it becomes quite difficult to assign ratings to these attributes based on numeric values. Therefore, the decision-making process relies on an idiosyncratic finding of the decision-makers which is in practice fuzzy with uncertainities. Hence, this article is a case study that deals with a hierarchy MCDM approach in accordance with the fuzzy logic and VIKOR method to solve a car purchasing problem.

Exploring travelers’ decision-making styles

2018 ◽  
Vol 30 (1) ◽  
pp. 618-636 ◽  
Author(s):  
Hilmi A. Atadil ◽  
Ercan Sirakaya-Turk ◽  
Fang Meng ◽  
Alain Decrop
Keyword(s):  
Decision Making ◽  
Strong Relationship ◽  
Decision Makers ◽  
Destination Image ◽  
Cluster Approach ◽  
Content Type ◽  
Tourism Studies ◽  
Decision Making Styles ◽  
Attitudinal Characteristics ◽  
Practical Implications

Purpose The purpose of this study is to profile market segments using travelers’ decision-making styles (DMS) as segmentation bases and to identify similarities and differences between traveler segments regarding a series of psychographic and attitudinal characteristics. Design/methodology/approach Data are gathered from a sample of 426 travelers in Dubai and Shanghai via self-reported surveys. Analyses included factor, k-means cluster, discriminant and MANOVA. Findings Study findings reveal significant differences among the rational, adaptive and daydreamer decision-makers’ segments in their behavioral and attitudinal characteristics with respect to tourism involvement and destination images. Practical implications Findings provide important practical implications for generating effective marketing and positioning strategies based on the identified attitudinal characteristics of the traveler segments for destination marketing organizations. Originality/value A stream of recent tourism studies shows a strong relationship between tourism involvement and destination images, yet very little research has tackled the issue of how these critical variables can be affected by individuals’ decision-making styles. This study explores and tests the relationships among DMS, tourism involvement and destination image using a factor-cluster approach.

AN APPROACH FOR COMBINING LINGUISTIC AND NUMERICAL INFORMATION BASED ON THE 2-TUPLE FUZZY LINGUISTIC REPRESENTATION MODEL IN DECISION-MAKING

2000 ◽  
Vol 08 (05) ◽  
pp. 539-562 ◽  
Author(s):  
F. HERRERA ◽  
L. MARTINEZ
Keyword(s):  
Decision Making ◽  
Linguistic Information ◽  
Loss Of Information ◽  
Linguistic Representation ◽  
Representation Model ◽  
Decision Making Problem ◽  
Linguistic Term ◽  
Multi Attribute Decision Making ◽  
Fuzzy Linguistic ◽  
Transformation Processes

In this paper we shall develop a procedure for combining numerical and linguistic information without loss of information in the transformation processes between numerical and linguistic information, taking as base for representing the information the 2-tuple fuzzy linguistic representation model. We shall analyze the conditions to impose the linguistic term set in order to ensure that the combination procedure does not produce any loss of information. Afterwards the aggregation process will be applied to a decision procedure over a multi-attribute decision-making problem dealing with numerical and linguistic information, that is, with qualitative and quantitative attributes.

scholarly journals DETERMINING WEIGHTS OF FUZZY ATTRIBUTES FOR MULTI-ATTRIBUTE DECISION-MAKING PROBLEMS BASED ON CONSENSUS OF EXPERT OPINIONS

2015 ◽  
Vol 21 (5) ◽  
pp. 738-755 ◽  
Author(s):  
Seyed Hossein RAZAVI HAJIAGHA ◽  
Hannan Amoozad MAHDIRAJI ◽  
Shide Sadat HASHEMI ◽  
Zenonas TURSKIS
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Decision Makers ◽  
Expert Opinions ◽  
Decision Making Problem ◽  
Order Preference ◽  
Multi Attribute Decision Making ◽  
Group Opinion ◽  
Selection Of

An important objective of a group decision-making problem is to determine the weights of attributes that are given by experts participating in the decision-making process. Since different decision-makers have unequal importance in decision-making, a series of studies focused on finding a set of appropriate weights for experts participating in a decision problem. In this paper, the problem of weight determination among decision-makers is investigated by extending an algorithm taken from the technique for order preference by similarity-to-ideal solution. In this case, a pair of most compromising and least compromising solutions is derived from individual judgments of decision-makers and then, these solutions are applied as the bases for determining the magnitude of individual alignment with the group opinion by using a closeness coefficient approach. Determining the weights of decision-makers, the group decision-making problem is then solved. Application of the proposed method is illustrated by a numerical example for the selection of a maintenance strategy.

The novel entropy measurements of Z+-numbers and their application on multi-attribute decision making problem

2021 ◽  
Vol 40 (1) ◽  
pp. 131-148
Author(s):  
Min-Chao Wu ◽  
Jun-Jun Mao ◽  
Ai-Ting Yao ◽  
Tao Wu
Keyword(s):  
Decision Making ◽  
Programming Model ◽  
Weight Vector ◽  
Cross Entropy ◽  
The Novel ◽  
Probability Models ◽  
Decision Making Problem ◽  
Promethee Method ◽  
Multi Attribute Decision Making ◽  
Cut Set

Z+-numbers, which carry more information than Z-numbers, are studied in this paper. Based on existed models, two more scientific and reasonable probability models of Z+-numbers are developed. In order to utilize Z+-numbers to solve practical problems, the α-cut set of Z+-numbers and corresponding utility function are proposed. Meanwhile, according to the structure of Z+-numbers, the entropy, cross-entropy and comprehensive cross-entropy are introduced to measure the uncertainty and fuzziness of Z+-numbers information. Furthermore, a linear programming model based on proposed three kinds of entropy is designed to obtain the weight vector of criteria in decision-making problems. Finally, we provide an example by selecting an optimal design of electricity vehicles charge station(DEVCS) combined the PROMETHEE method with Z+-numbers, and the feasibility of the proposed method are verified.

Spherical uncertain linguistic Hamacher aggregation operators and their application on achieving consistent opinion fusion in group decision making

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Muhammad Qiyas ◽  
Saleem Abdullah ◽  
Muhammad Naeem
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Aggregation Operator ◽  
Aggregation Operators ◽  
Content Type ◽  
Operational Laws ◽  
Decision Making Problem ◽  
Multi Attribute Decision Making ◽  
New Type

PurposeThe aim of this research is to establish a new type of aggregation operator based on Hamacher operational law of spherical uncertain linguistic numbers (SULNs).Design/methodology/approachFirst, the authors define spherical uncertain linguistic sets and develop some operational laws of SULNs. Furthermore, the authors extended these operational laws to the aggregation operator and developed spherical uncertain linguistic Hamacher averaging and geometric aggregation operators.FindingsThe authors were limited in achieving a consistent opinion on the fusion in group decision-making problem with the SULN information.Originality/valueIn order to give an application of the introduced operators, the authors first constrict a system of multi-attribute decision-making algorithm.

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