Two-stage weighted PROMETHEE II with results’ visualization

Kuncová, Martina; Seknickova, Jana

doi:10.1007/s10100-021-00788-9

Cited by 10 publications

(2 citation statements)

References 39 publications

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“…Akram et al [33] proposed a rough ELECTRE-II method with the specific structure, through which the diverse opinions of decision experts can be well handled. Kuncova et al [34] proposed a fuzzy rough PROMETHEE method which can evaluate the order of 14 regions of the Czech Republic in regard to economic indices. Liu et al [35] proposed a fuzzy rough PROMETHEE method to accomplish the process for optimal alternative selection.…”

Section: Introductionmentioning

confidence: 99%

A Rule-Based Decision Support Method Combining Variable Precision Rough Set and Stochastic Multi-Objective Acceptability Analysis for Multi-Attribute Decision-Making

Zhu

Liu

Zhang

et al. 2022

Mathematical Problems in Engineering

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In an open environment, the demands of users are diverse and dynamic because users can participate in product design from beginning to end. Owing to this, the disorderly and unplanned participation of users will greatly increase the complexity of multi-attribute decision-making (MADM) in the product design process. In order to ensure the smooth development of the open design process, the decision support model and method need to repeatedly provide decision makers (DMs) with necessary decision support information in a relatively short period of time, which can realize the evaluation of the scheme and improve the utilization efficiency of community resources. However, the process of eliciting preference information is complex, exhausting, inefficient, and time-consuming in existing methods, which will result in a poor decision-making. With the purpose of optimizing the eliciting process in MADM, a rule-based decision support method is proposed in this paper, where the process of eliciting preference information and decision-making are synchronized and guided by pre-extracted decision rules. The rules are deduced from comparison relations on attributes and their outcomes through the combination of variable precision rough set approach (VPRS) and stochastic multi-objective acceptability analysis (SMAA). With the concept of attribute reduction and approximation accuracy in rough set theory, the extracted rules could eliminate redundant attributes and assign the relative priority of preference information. Based on the extracted rules, the multi-attribute decision-making process could be carried out step by step in an orderly manner. In each step, DMs only need to provide partial preference information by non-quantitative statements according to extracted rules. Once the decision result is reliable enough, the eliciting and decision-making process can be terminated promptly. In order to validate the proposed approach, experiments of decision rule extraction are implemented, and the results show that the proposed approach is effective both in the weak rule extraction and the strong rule extraction.

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Section: Introductionmentioning

confidence: 99%

A Rule-Based Decision Support Method Combining Variable Precision Rough Set and Stochastic Multi-Objective Acceptability Analysis for Multi-Attribute Decision-Making

Zhu

Liu

Zhang

et al. 2022

Mathematical Problems in Engineering

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“…,Antanasijević et al (2017),Costa et al (2019),Belke (2020),Arsu and Ayçin (2021),Kuncova and Seknickova (2021) were determined by using the studies in the previous literature and given in Table 1. The last column of Table 1 also shows the characteristics of the criteria.…”

mentioning

confidence: 99%

Çok Kriterli Karar Verme Problemlerinde Duyarlılık Analizi

Demir

Arslan

2022

Ankara Hacı Bayram Veli Üniversitesi İktisadi Ve İdari Bilimler Fakültesi Dergisi

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The aim of this study is to propose a model of stability and sensitivity for the studies used in the implementation of multi-criteria decision making (MCDM). In this context, it is proposed to use the steps "sensitivity analysis based on the variation of criterion weight, sensitivity analysis based on sequence reversal feature and comparison analysis with results from different sorting methods" for stability and sensitivity analysis. In the implementation part of the method, the Fragile Five countries were used as criteria for the unemployment rate, state budget, GDP growth, inflation, current account balance, risk premium for these countries. The criteria were weighted with MEREC and the ordering of alternatives was carried out with WISP. In the application phase of the method, it was found that the model was sensitive to changes in weight coefficients with different weights assigned to criteria over 22 scenarios. It has been observed that the model provides valid results in a dynamic environment through 4 different scenarios created in the sequence inversion step of the model. For the reliability of the MEREC-WISP-based model, a ranking comparison was made with some commonly used methods such as PIV, CoCoSo, COPRAS, WEDBA, TOPSIS and SAW and the results were found to have a high correlation.

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