Assessing Normalization Techniques for Simple Additive Weighting Method

Vafaei, Nazanin; Ribeiro, Rita A.; Camarinha-Matos, Luís M.

doi:10.1016/j.procs.2022.01.156

Cited by 57 publications

(28 citation statements)

References 10 publications

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“…Only DN2 was suitable when combining the SAW method with four DN methods (DN2-DN4 and DN6) [22]. Only DN9 is considered suitable when combining the ROV method with eight methods (DN2-DN4, DN6, DN7, DN9, DN11, and DN12) [23].…”

Section: Literature Reviewmentioning

confidence: 99%

Selection of Suitable Data Normalization Method to Combine with the CRADIS Method for Making Multi-Criteria Decision

Hà¹

2023

Applied Engineering Letters

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Compromise Ranking of Alternatives from Distance to Ideal Solution (CRADIS) is a new MCDM method (discovered in 2022). It is built on a combination of three well-known methods, including Additive Ratio Assessment (ARAS), Measurement Alternatives and Ranking according to Compromise Solution (MARCOS), and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). This method has the advantage of being resistant to the rank inversion phenomenon. However, if only the available data normalization (DN) method in this method is used, this method will only be usable in some cases. This study investigated the suitability of twelve data normalization methods combined with the CRADIS method. The solutions in four cases of four different fields were ranked using these twelve combination methods. Using these methods, the ranked results were compared with those of other MCDM methods. Four DN methods were appropriate in combination with the CRADIS method. The application scope of CRADIS method can be extended when using this DN method.

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Section: Literature Reviewmentioning

confidence: 99%

Selection of Suitable Data Normalization Method to Combine with the CRADIS Method for Making Multi-Criteria Decision

Hà¹

2023

Applied Engineering Letters

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“…The result of calculating the greater value of Vi states that the alternative Ai is the best alternative. In other words, the weight of the criterion (w) is multiplied by all the values of each participant (r) for each criterion and added [13].…”

Section: Data Analysis Using Saw Methodsmentioning

confidence: 99%

Effect of microwave heating on sensory quality assessment of butterfly pea (Clitoria ternatea L.) flower using simple additive weighting

Juanda,

Hartuti,

Agustina

2024

IOP Conf. Ser.: Earth Environ. Sci.

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Drying of butterfly pea flowers is necessary to extend its shelf life and to use it in various functional food products, such as various types of drinks and foods, as well as natural colouring materials. Currently, the use of butterfly pea flowers in functional drinks is growing in various regions, including Indonesia. This research aims to determine butterfly pea flowers’ microwave power and drying time based on sensory analysis using the SAW (simple additive weighting) method. The hedonic test was also conducted to assess the level of preference of panellists for steeping butterfly pea flower tea based on pre-set parameters to obtain the tea preferences. Panellists perform sensory assessments determined based on a numerical scale of 1-7, where value 7 is strongly like, value 6 is like, value 5 is somewhat like, value 4 is neutral, value 3 is somewhat dislike, value 2 is dislike, and value 1 is strongly dislike. The results showed that the level of preference for alternative treatment to sensory quality, consisting of criteria of colour, flavour, taste, and aftertaste, it was known that alternative treatment with rank 1 was obtained at 180 watts microwave power treatment and drying time for 17 minutes.

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“…From the perspective of controlling CO2 emissions, to achieve the coordinated development of energy, economy and society, we need a reasonable allocation of energy. Therefore, the problem to be studied is a continuous decision-making problem, and a weighted algorithm is adopted [9][10].…”

Section: Carbon Emission Control Systemmentioning

confidence: 99%

Research on multi-objective optimization of energy power system under low carbon constraints

2023

J. Phys.: Conf. Ser.

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The optimization of energy saving and application of power system under low carbon constraint is the improvement of energy security theory and economic theory. To realize the optimization of China’s energy structure, develop low-carbon energy, and strengthen the reform of the energy structure, it is conducive to promoting the development of China’s low-carbon economy and achieving the goal of energy conservation and emission reduction. In order to realize the sustainable development of the economy, energy, and environment, a multi-objective optimization study of this paper proposes an energy power system based on low carbon constraints. The multi-objective optimization structure of the energy power system is analyzed, the model assumptions are established, the decision variables are selected, the objective function is set, the constraints are determined, and the multi-objective optimization model of the energy power system under the low-carbon constraints is constructed to realize the multi-objective optimization of the energy power system. It can be seen from the analysis of the optimization results that the use of this optimization model can effectively reduce CO2 emissions, thereby promoting the healthy development of a low-carbon economic system.

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Assessing Normalization Techniques for Simple Additive Weighting Method

Cited by 57 publications

References 10 publications

Selection of Suitable Data Normalization Method to Combine with the CRADIS Method for Making Multi-Criteria Decision

Selection of Suitable Data Normalization Method to Combine with the CRADIS Method for Making Multi-Criteria Decision

Effect of microwave heating on sensory quality assessment of butterfly pea (Clitoria ternatea L.) flower using simple additive weighting

Research on multi-objective optimization of energy power system under low carbon constraints

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