Multi-attribute decision making : a test on the impact of data attributes dependency

2007 ◽  
Author(s):  
Wei Li
Keyword(s):  
Decision Making ◽  
Multi Attribute Decision Making ◽  
The Impact

scholarly journals An m-Polar Fuzzy PROMETHEE Approach for AHP-Assisted Group Decision-Making

2020 ◽  
Vol 25 (2) ◽  
pp. 26 ◽  
Author(s):  
Muhammad Akram ◽  
Shumaiza ◽  
José Alcantud
Keyword(s):  
Decision Making ◽  
Pairwise Comparison ◽  
Preference Ranking ◽  
Promethee Ii ◽  
Partial Ranking ◽  
Preference Functions ◽  
Multi Attribute Decision Making ◽  
Ranking Of Alternatives ◽  
The Impact ◽  
Fuzzy Promethee

The Analytical Hierarchy Process (AHP) is arguably the most popular and factual approach for computing the weights of attributes in the multi-attribute decision-making environment. The Preference Ranking Organization Method for Enrichment of Evaluations (PROMETHEE) is an outranking family of multi-criteria decision-making techniques for evaluating a finite set of alternatives, that relies on multiple and inconsistent criteria. One of its main advantages is the variety of admissible preference functions that can measure the differences between alternatives, in response to the type and nature of the criteria. This research article studies a version of the PROMETHEE technique that encompasses multipolar assessments of the performance of each alternative (relative to the relevant criteria). As is standard practice, first we resort to the AHP technique in order to quantify the normalized weights of the attributes by the pairwise comparison of criteria. Afterwards the m-polar fuzzy PROMETHEE approach is used to rank the alternatives on the basis of conflicting criteria. Six types of generalized criteria preference functions are used to measure the differences or deviations of every pair of alternatives. A partial ranking of alternatives arises by computing the positive and negative outranking flows of alternatives, which is known as PROMETHEE I. Furthermore, a complete ranking of alternatives is achieved by the inspection of the net flow of alternatives, and this is known as PROMETHEE II. Two comparative analysis are performed. A first study checks the impact of different types of preference functions. It considers the usual criterion preference function for all criteria. In addition, we compare the technique that we develop with existing multi-attribute decision-making methods.

scholarly journals A Novel Multi-Attribute Decision-Making Algorithm for Landfill Site Selection Based on Q-Rung Orthopair Probabilistic Hesitant Fuzzy Power Weight Muirhead Mean Operator

2021 ◽  
Author(s):  
Yaojun Ren ◽  
Xiujiu Yuan ◽  
Ruojing Lin
Keyword(s):  
Decision Making ◽  
Decision Maker ◽  
Site Selection ◽  
Landfill Site ◽  
Decision Makers ◽  
Parameter Analysis ◽  
Power Weight ◽  
Landfill Site Selection ◽  
Multi Attribute Decision Making ◽  
The Impact

Abstract BackgroundWith the rapid development of economy and the acceleration of urbanization, the garbage produced by urban residents also increases with the increase of population. In many big cities, the phenomenon of "garbage siege" has seriously affected the development of cities and the lives of residents. Sanitary landfill is an important way of municipal solid waste disposal. However, due to the restriction of social, environmental and economic conditions, landfill site selection has become a very challenging task. In addition, landfill site selection is full of uncertainty and complexity due to the lack of cognitive ability of decision-makers and the existence of uncertain information in the decision-making process.MethodsA novel multi-attribute decision making method based on q-rung orthopair probabilistic hesitant fuzzy power weight Muirhead mean (q-ROPHFPWMM) operator is proposed in this paper, which can solve the problem of landfill site selection well. This method uses probability to represent the hesitance of decision maker and retains decision information more comprehensively. The negative effect of abnormal data on the decision result is eliminated by using the power average operator. Muirhead mean operator is used to describe the correlation between attributes. ResultsAn example of landfill site selection is given to verify the effectiveness of the proposed method, and the advantages of the proposed method are illustrated by parameter analysis and comparative analysis. ConclusionThe q-ROPHFPWMM operator can describe the correlation between any evaluation factors and effectively reduce the impact of unreasonable evaluation information given by decision makers on the results. In addition, this method has a wider space for information expression, gives the decision maker a great degree of freedom in decision-making.

scholarly journals Some Interval Neutrosophic Dombi Power Bonferroni Mean Operators and Their Application in Multi–Attribute Decision–Making

Symmetry ◽  
2018 ◽  
Vol 10 (10) ◽  
pp. 459 ◽  
Author(s):  
Qaisar Khan ◽  
Peide Liu ◽  
Tahir Mahmood ◽  
Florentin Smarandache ◽  
Kifayat Ullah
Keyword(s):  
Decision Making ◽  
Hybrid Structure ◽  
Aggregation Operators ◽  
Neutrosophic Sets ◽  
Bonferroni Mean ◽  
Operational Laws ◽  
Multi Attribute Decision Making ◽  
Geometric Bonferroni Mean ◽  
Dombi Operations ◽  
The Impact

The power Bonferroni mean (PBM) operator is a hybrid structure and can take the advantage of a power average (PA) operator, which can reduce the impact of inappropriate data given by the prejudiced decision makers (DMs) and Bonferroni mean (BM) operator, which can take into account the correlation between two attributes. In recent years, many researchers have extended the PBM operator to handle fuzzy information. The Dombi operations of T-conorm (TCN) and T-norm (TN), proposed by Dombi, have the supremacy of outstanding flexibility with general parameters. However, in the existing literature, PBM and the Dombi operations have not been combined for the above advantages for interval-neutrosophic sets (INSs). In this article, we first define some operational laws for interval neutrosophic numbers (INNs) based on Dombi TN and TCN and discuss several desirable properties of these operational rules. Secondly, we extend the PBM operator based on Dombi operations to develop an interval-neutrosophic Dombi PBM (INDPBM) operator, an interval-neutrosophic weighted Dombi PBM (INWDPBM) operator, an interval-neutrosophic Dombi power geometric Bonferroni mean (INDPGBM) operator and an interval-neutrosophic weighted Dombi power geometric Bonferroni mean (INWDPGBM) operator, and discuss several properties of these aggregation operators. Then we develop a multi-attribute decision-making (MADM) method, based on these proposed aggregation operators, to deal with interval neutrosophic (IN) information. Lastly, an illustrative example is provided to show the usefulness and realism of the proposed MADM method. The developed aggregation operators are very practical for solving MADM problems, as it considers the interaction among two input arguments and removes the influence of awkward data in the decision-making process at the same time. The other advantage of the proposed aggregation operators is that they are flexible due to general parameter.

scholarly journals Understanding the Role of Visualizations on Decision Making: A Study on Working Memory

Informatics ◽  
2020 ◽  
Vol 7 (4) ◽  
pp. 53
Author(s):  
Sung-Hee Kim
Keyword(s):  
Decision Making ◽  
Working Memory ◽  
User Study ◽  
Phonological Loop ◽  
Decision Quality ◽  
Use Of Data ◽  
Interactive Visualizations ◽  
Multi Attribute Decision Making ◽  
The Impact

The use of data visualization is increasing; however, there is little empirical explanation for how it supports users. Our goal in this paper is to deepen our understanding of the role of interactive visualizations in a particular context of decision making. Specifically, we attempt to understand the role of the working memory system, which is a concept to understand the mechanism of the processing and temporary storage of information in variety of cognitive tasks. We compared two interfaces, SimulSort and its non-visual counterpart Typical Sorting, with a multi-attribute decision-making problem. Because decision outcomes are known to be affected by the limitations of a person’s working memory, we conducted a crowdsourcing-based user study using SimulSort to understand how working memory, especially the phonological loop, can benefit from the using visualizations. We examined the impact on working memory with a well known dual-task methodology by designing a concurrent task to tap into the main decision-making task. The experiment was conducted with a total of 137 participants and an ordered logistic regression using a proportional odds model was applied to analyze the decision quality. The results supported the hypothesis that when using SimulSort, participants required less working memory than they required with Typical Sorting to accomplish the multi-attribute decision-making task even though SimulSort outperformed Typical Sorting in terms of decision quality. We also provide methodologies to conduct working memory studies by implementing an articulatory suppression task on crowdsourcing platforms in which experimenters have less control over the participants.

Quota Women Are Threatening to Men

2017 ◽  
Vol 76 (3) ◽  
pp. 107-116 ◽  
Author(s):  
Klea Faniko ◽  
Till Burckhardt ◽  
Oriane Sarrasin ◽  
Fabio Lorenzi-Cioldi ◽  
Siri Øyslebø Sørensen ◽  
...  
Keyword(s):  
Decision Making ◽  
Organizational Performance ◽  
Gender Stereotypes ◽  
Perceived Threat ◽  
Preferential Treatment ◽  
Public Sector Employees ◽  
Different Types ◽  
Low Levels ◽  
Women In Decision Making ◽  
The Impact

Abstract. Two studies carried out among Albanian public-sector employees examined the impact of different types of affirmative action policies (AAPs) on (counter)stereotypical perceptions of women in decision-making positions. Study 1 (N = 178) revealed that participants – especially women – perceived women in decision-making positions as more masculine (i.e., agentic) than feminine (i.e., communal). Study 2 (N = 239) showed that different types of AA had different effects on the attribution of gender stereotypes to AAP beneficiaries: Women benefiting from a quota policy were perceived as being more communal than agentic, while those benefiting from weak preferential treatment were perceived as being more agentic than communal. Furthermore, we examined how the belief that AAPs threaten men’s access to decision-making positions influenced the attribution of these traits to AAP beneficiaries. The results showed that men who reported high levels of perceived threat, as compared to men who reported low levels of perceived threat, attributed more communal than agentic traits to the beneficiaries of quotas. These findings suggest that AAPs may have created a backlash against its beneficiaries by emphasizing gender-stereotypical or counterstereotypical traits. Thus, the framing of AAPs, for instance, as a matter of enhancing organizational performance, in the process of policy making and implementation, may be a crucial tool to countering potential backlash.

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