Methods for Determining the Group Ranking of Alternatives for Incomplete Expert Rankings

2020 ◽  
pp. 217-226
Author(s):  
Hrygorii Hnatiienko ◽  
Nataliia Tmienova ◽  
Alexander Kruglov
Keyword(s):  
Group Ranking ◽  
Ranking Of Alternatives

scholarly journals Uncertainty of the implementation time of geodynamic monitoring system in multi-criteria ranking of alternatives

2020 ◽  
Vol 17 (3) ◽  
pp. 1249
Author(s):  
O.R. Kuzichkin ◽  
I.V. Loginov ◽  
V.T. Eremenko ◽  
S. V. Eremenko ◽  
G.S. Vasilyev ◽  
...  
Keyword(s):  
Monitoring System ◽  
Time Factors ◽  
Monitoring Systems ◽  
Time Varying ◽  
Functional Characteristics ◽  
Quality Properties ◽  
Geodynamic Monitoring ◽  
Implementation Time ◽  
Ranking Of Alternatives ◽  
Technical Solutions

<p>The paper deals with the problem of ranking alternatives to geodynamic monitoring systems in the case of uncertainty of their implementation time. The problem is characterized by the fact that the choice of alternatives and the effect of it depends on the quality properties of the applied organizational and technical solutions, taking into account the time of implementation. The ordering of alternatives is proposed taking into account the uncertainty of the implementation time factors. Ranking is realized by comparing the trees of functional characteristics of alternatives taking into account the compliance of their characteristics with time-varying requirements. The scope of the proposed method is the choice of configurations of geodynamic monitoring systems with significant differences in the implementation time of alternatives.</p>

Privacy Preserving Group Ranking

2012 ◽  
Author(s):  
Lingjun Li ◽  
Xinxin Zhao ◽  
Guoliang Xue ◽  
Gabriel Silva
Keyword(s):  
Privacy Preserving ◽  
Group Ranking

Meaningful Composite Benefit Measures

1975 ◽  
Vol 19 (4) ◽  
pp. 381-387
Author(s):  
David L. Bitters ◽  
Gordon M. Clark
Keyword(s):  
Functional Form ◽  
Ranking Of Alternatives ◽  
The Individual ◽  
System Analyst

The structure of composite benefit measures that provide an overall ranking of alternatives for the system analyst is investigated. These composite benefit measures are functions of individual benefit measures, and the individual benefit measures may give conflicting rankings of the various alternatives. A functional form for the composite benefit measure is identified that is symantically meaningful and avoids scaling problems. In addition a method for estimating coefficients in this composite benefit measure is outlined.

scholarly journals Uncertain Multiplicative Language Decision Method Based on Group Compromise Framework for Evaluation of Mobile Medical APPs in China

2020 ◽  
Vol 17 (8) ◽  
pp. 2858
Author(s):  
Junchang Li ◽  
Jiantong Zhang ◽  
Ye Ding
Keyword(s):  
Health Management ◽  
Medical Application ◽  
Assessment System ◽  
Medical Apps ◽  
Attribute Weight ◽  
Group Ranking ◽  
Medical App ◽  
Multiple Attribute ◽  
The Individual ◽  
Mobile Medical Apps

The mobile medical application (M-medical APP) can optimize medical service process and reduce health management costs for users, which has become an important complementary form of traditional medical services. To assist users including patients choose the ideal M-medical APP, we proposed a novel multiple attribute group decision making algorithm based on group compromise framework, which need not determine the weight of decision-maker. The algorithm utilized an uncertain multiplicative linguistic variable to measure the individual original preference to express the real evaluation information as much as possible. The attribute weight was calculated by maximizing the differences among alternatives. It determined the individual alternatives ranking according to the net flow of each alternative. By solved the 0–1 optimal model with the objective of minimizing the differences between individual ranking, the ultimate group compromise ranking was obtained. Then we took 10 well-known M-medical APPs in Chinese as an example, we summarized service categories provided for users and constructed the assessment system consisting of 8 indexes considering the service quality users are concerned with. Finally, the effectiveness and superiority of the proposed method and the consistency of ranking results were verified, through comparing the group ranking results of 3 similar algorithms. The experiments show that group compromise ranking is sensitive to attribute weight.

Discovering Consensus Preferences Visually Based on Gower Plots

2018 ◽  
Vol 17 (03) ◽  
pp. 741-761
Author(s):  
Li-Ching Ma
Keyword(s):  
Group Consensus ◽  
Visual Aids ◽  
Ranking List ◽  
Consensus Sequences ◽  
Group Ranking ◽  
Data Mining Approach ◽  
Search Processes ◽  
Ranking Problems ◽  
Visually Based ◽  
Made In

Group-ranking problems are widely encountered decision problems which combine personal preferences to form an integrated group priority; however, providing support to solve group-ranking problems is difficult because each person has his/her own viewpoint regarding how such decisions should be made. In addition, many researchers have shown that visual aids are useful in helping users comprehend decision backgrounds. Therefore, determining how to support the group-ranking process and providing visual aids is an important issue. This study proposes a novel graphical approach to discover group consensus sequences. First, a counting-based data mining approach is constructed to discover a consensus preference matrix. Second, an ordinal Gower plot can be drawn whereby group consensus sequences can be directly observed. Unlike previous methods, the proposed approach can discover group consensus sequences without involving tedious candidate generation and exhaustive search processes, derive a total ranking list, as well as provide visual aids to users.

On the Use of Probit-Based Models for Ranking Data Analysis

2019 ◽  
Vol 2673 (4) ◽  
pp. 229-240 ◽  
Author(s):  
Gopindra S. Nair ◽  
Chandra R. Bhat ◽  
Ram M. Pendyala ◽  
Becky P. Y. Loo ◽  
William H. K. Lam
Keyword(s):  
Data Analysis ◽  
Preference Elicitation ◽  
Ordered Probit ◽  
Common Method ◽  
Ordered Logit ◽  
Ranking Data ◽  
Consumer Surveys ◽  
Ranking Of Alternatives ◽  
The Common

In consumer surveys, more information per response regarding preferences of alternatives may be obtained if individuals are asked to rank alternatives instead of being asked to select only the most-preferred alternative. However, the latter method continues to be the common method of preference elicitation. This is because of the belief that ranking of alternatives is cognitively burdensome. In addition, the limited research on modeling ranking data has been based on the rank ordered logit (ROL) model. In this paper, we show that a rank ordered probit (ROP) model can better utilize ranking data information, and that the prevalent view of ranking data as not being reliable (because of the attenuation of model coefficients with rank depth) may be traced to the use of a misspecified ROL model rather than to any cognitive burden considerations.

scholarly journals Cold Chain Logistics Management of Medicine with an Integrated Multi-Criteria Decision-Making Method

2019 ◽  
Vol 16 (23) ◽  
pp. 4843 ◽  
Author(s):  
Zhi Wen ◽  
Huchang Liao ◽  
Ruxue Ren ◽  
Chunguang Bai ◽  
Edmundas Kazimieras Zavadskas ◽  
...  
Keyword(s):  
Decision Making ◽  
Multiple Criteria Decision Making ◽  
Cold Chain ◽  
Solution Methods ◽  
Criteria Weights ◽  
Ranking Of Alternatives ◽  
And Storage ◽  
Selection Of

Medicine is the main means to reduce cancer mortality. However, some medicines face various risks during transportation and storage due to the particularity of medicines, which must be kept at a low temperature to ensure their quality. In this regard, it is of great significance to evaluate and select drug cold chain logistics suppliers from different perspectives to ensure the quality of medicines and reduce the risks of transportation and storage. To solve such a multiple criteria decision-making (MCDM) problem, this paper proposes an integrated model based on the combination of the SWARA (stepwise weight assessment ratio analysis) and CoCoSo (combined compromise solution) methods under the probabilistic linguistic environment. An adjustment coefficient is introduced to the SWARA method to derive criteria weights, and an improved CoCoSo method is proposed to determine the ranking of alternatives. The two methods are extended to the probabilistic linguistic environment to enhance the applicability of the two methods. A case study on the selection of drug cold chain logistics suppliers is presented to demonstrate the applicability of the proposed integrated MCDM model. The advantages of the proposed methods are highlighted through comparative analyses.

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