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MLP-COMET-based decision model re-identification for continuous decision-making in the complex network environment

Kizielewicz Bartłomiej, Więckowski Jakub, Jankowski Jarosław

Annals of Computer Science and Information Systems

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2023

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Vol. 35

591--602

EN

In recent years, complex networks have gained significant attention for their practical potential in data analysis and decision-making. However, assessing node relevance in complex networks poses challenges, including subjectivity and difficulty reproducing criteria relationships. To address these issues, we propose MLP-COMET. This novel approach combines the Multi-Layer Perceptron (MLP) with the Characteristic Objects Method (COMET) in Multi-Criteria Decision Analysis (MCDA). MLP-COMET aims to re-identify decision models using MLP to evaluate characteristic objects. We evaluate the approach to assessing the complex network and demonstrate its effectiveness in evaluating without heavy reliance on domain experts. The MLP-COMET performance is evaluated through ranking comparisons, showing a strong correlation with reference expert rankings. We also analyze the impact of training sample size and number of characteristic objects on ranking similarity, observing high stability and similarity using the $r\_w$ metric. MLP-COMET offers an effective and reliable tool for evaluating complex networks and facilitating decision-making processes.

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Towards the identification of MARCOS models based on intuitionistic fuzzy score functions

Kizielewicz Bartłomiej, Paradowski Bartosz, Więckowski Jakub, Sałabun Wojciech

Annals of Computer Science and Information Systems

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2022

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Vol. 30

789--798

EN

We encounter uncertainty in many areas. In decision-making, it is an aspect that allows for better modeling of real-world problems. However, many methods rely on crisp numbers in their calculations. It makes it necessary to use techniques that perform this conversion. In this paper, we address the problem of score functions assessment regarding their effectiveness and usefulness in the decision-making field. The selected methods were used to convert the intuitionistic fuzzy set matrix into crisp data, then used in the multi-criteria assessment. Managing the theoretical problem showed that the used techniques provide high similarity values. Moreover, they proved to be helpful when dealing with intuitionistic fuzzy sets in the decision-making area.

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A novel iterative approach to determining compromise rankings

Kizielewicz Bartłomiej, Shekhovtsov Andrii, Sałabun Wojciech

Annals of Computer Science and Information Systems

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2022

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Vol. 30

783--787

EN

In many cases involving multi-criteria decision-making, we need compromise solutions. This is a crucial aspect due to the specific characteristics of decision problems. However, the proposed trade-off approaches are often complex to verify to what extent they are reliable. Therefore, this paper proposes a new iterative approach based on decision option evaluations from selected multi-criteria decision-making methods, i.e., TOPSIS, VIKOR, and SPOTIS. The obtained results have high similarity among each other, which was measured by Spearman's weighted correlation coefficient and WS ranking similarity coefficient. Furthermore, the proposed approach showed high efficiency and adaptability of the generated results.

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Towards Objectification of Multi-Criteria Assessments: a Comparative Study on MCDA Methods

Bączkiewicz Aleksandra, Wątróbski Jarosław, Kizielewicz Bartłomiej, Sałabun Wojciech

Annals of Computer Science and Information Systems

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2021

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Vol. 25

417--425

EN

Objective evaluation in problems considering many, often conflicting criteria is challenging for the decision-maker. This paper presents an approach based on MCDA methods to objectify evaluations in the camera selection problem. The proposed approach includes three MCDA methods, TOPSIS, VIKOR, COMET, and two criterion weighting techniques. Two ranking similarity coefficients were used to compare the resulting rankings of the alternatives: WS and rw. The performed research confirmed the importance of the appropriate selection of multi-criteria decision-making methods for the solved problem and the relevance of comparative analysis in method selection and construction of objective rankings of alternatives.

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Effect of Criteria Range on the Similarity of Results in the COMET Method

Shekhovtsov Andrii, Więckowski Jakub, Kizielewicz Bartłomiej, Sałabun Wojciech

Annals of Computer Science and Information Systems

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2021

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Vol. 25

453--457

EN

Defining input values in the decision-making process can be done with appropriate methods or based on expert knowledge. It is essential to ensure that the values are adequate for the problem to be solved in both cases. There may be situations where values are overestimated, and it should be checked whether this affects the final results. In this paper, the Characteristic Objects Method (COMET) was used to investigate the overestimation effect on the final rankings. The decision matrixes with a different number of alternatives and criteria were assessed The obtained results were compared using the WS similarity coefficient and Spearman's weighted correlation coefficient. The study showed that overestimation has a significant effect on the rankings. A larger number of criteria has a positive effect on the correlation strength of the compared rankings. In contrast, a large overestimation of characteristic values has a negative effect on the similarity of the results.