Selecting the Best Normalization Technique for ROV Method: Towards a Real Life Application

Ersoy, Nazlı

doi:10.35378/gujs.767525

Cited by 21 publications

(22 citation statements)

References 34 publications

(46 reference statements)

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“…In the literature, numerous comparative studies that analyse the impact of normalization methods on the decision outcome of a particular MCDM technique have been proposed [1,2,5,21,22,[24][25][26][27][28][29][30]. For instance, [3] presented a model to determine the most appropriate normalization technique for the Range of Value (ROV) method. A real case was analysed and eight different normalization techniques where compared with each other based on a multi-stage framework.…”

Section: Related Workmentioning

confidence: 99%

“…Additionally, in MCDM, normalization methods map the different measurements unit of the performance rating into similar (nondimensional) unit [5]. In this study, the five well known normalization techniques used are presented in Table 2 and analysis on their effects on the contextual analysis of web service selection [1,3,4,22,24]. The benefit formula imply "Higher the better", while cost formula imply "lower the better" [27].…”

Section: Normalization Instrumentsmentioning

confidence: 99%

“…Therefore, a pre-treatment to define the criteria on the same scale is required. This process is referred to as normalization [3]. MCDM techniques utilize normalization methods to transform the dis-similar units of performance rating measurements into a comparable (non-dimensional) unit.…”

Section: Introductionmentioning

confidence: 99%

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Influence of Normalization Techniques on Multi-criteria Decision-making Methods

Mhlanga

Lall

2022

J. Phys.: Conf. Ser.

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One of the most significant steps in solving multi criteria decision-making (MCDM) problems is the normalization of the decision matrix. The consideration for the normalization of the data in a judgment matrix is an essential step as it can influence the ranking list. This study investigates the effects of normalization on an AHP-VIKOR hybrid method in the selection of Web services. The Web services considered in this research offer similar functionalities but with different Quality of Services (QoS). For the purpose of this study, ten web services were selected. Each of these services were evaluated against five difference QoS requirements namely, response time, throughput rate, latency, availability, and reliability to determine the most appropriate Web services. The five normalization techniques employed are linear sum, linear max, linear max-min, enhanced accuracy and vector normalization. It was observed that different ranking lists are produced when applying different normalization techniques to the VIKOR method and normalization has an influence on the final ranking list.

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Section: Related Workmentioning

confidence: 99%

Section: Normalization Instrumentsmentioning

confidence: 99%

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Influence of Normalization Techniques on Multi-criteria Decision-making Methods

Mhlanga

Lall

2022

J. Phys.: Conf. Ser.

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“…The results are presented in Table 5. Calculate the rating (Hi) for each option according to the formula (22) and the results have also been included in Table 5. The results of the ranking of options have also been performed and are also presented in this Table 5.…”

Section: Examplementioning

confidence: 99%

“…However, different multi-criteria decision making methods using different data normalization methods. This will result in different ranking results [20][21][22]. In the next section, several of these cases will be discussed in more detail.…”

Section: Introductionmentioning

confidence: 99%

Expanding Data Normalization Method to CODAS Method for Multi-Criteria Decision Making

Trung¹

2022

Applied Engineering Letters

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Data normalization is the conversion of quantities of different dimensions to the same dimensionless form, which is required in multicriteria decision making (MCDM). The choice of data normalization method has a direct influence on the decision-making results. This study presents the combination of CODAS (COmbinative Distance-based ASsessment) method with six different data normalization methods including Linear normalization, Max -Min linear normalization, Vector normalization, Sum linear normalization, Logarithmic normalization, Max linear normalization . These six combinations have been applied in turn in three different examples. The number of alternatives, the number of criteria, and the method of the weight calculation in these examples are also different. From the results it was reported that only the combination of CODAS and Logarithmic normalization was not suitable. The combination of CODAS with some other data normalization methods not mentioned in this study and it needs to be done in the near future. This task was covered in the last part of this paper.

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