Developing TOPSIS method using statistical normalization for selecting knowledge management strategies

Sarraf, Amin Zadeh; Mohaghar, Ali; Bazargani, Hossein

doi:10.3926/jiem.573

Cited by 36 publications

(16 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…In this context, the primary purpose of scaling is to provide the appropriate measurements or data structure for the proper method or analysis. Normalization is one of the critical processes used in scaling data (Jensen, 1984;Roberts, 1984;Lootsma, 1999;Tavşancıl, 2006;Kainulainen et al, 2009;Sarraf et al, 2013;Jahan & Edwards, 2015;Podviezko & Podvezko, 2015;Gardziejczyk & Zabicki, 2017).…”

Section: Introductionmentioning

confidence: 99%

Comparative Analysis of the Normalization Techniques in the Context of MCDM Problems

Ayteki̇n

2021

Decis. Mak. Appl. Manag. Eng.

View full text Add to dashboard Cite

NormNormalization is an essential step in data analysis and for MCDM methods. This study aims to outline the positive and negative features of the normalization techniques that can be used in MCDM problems. In order to compare the different normalization techniques, fourteen sets representing different scenarios of decision problems were used. According to the results, if the decision-maker chooses to take the alternative with the highest value in the criteria and avoid the one with the lowest value, or vice versa, optimization-based normalization techniques should be preferred, whereas the reference-based normalization techniques are considered appropriate for situations where there are ideal values determined by the decision-maker for each criterion. However, if the decision-maker believes that the values in the criteria do not represent the monotonous increasing or decreasing benefit/cost, then non-linear normalization techniques should be used. Also, in the event of a change in the conditions mentioned above, the decision maker may opt for mixed normalization techniques. However, some data structures, such as the presence of zero, and negative values in the decision matrix, can prevent the use of some normalization techniques. The choice of the normalization technique may also be affected by the problem of rank reversal, the range of normalized values, obtaining the same optimization aspect for all criteria, and the validity of results.

show abstract

Section: Introductionmentioning

confidence: 99%

Comparative Analysis of the Normalization Techniques in the Context of MCDM Problems

Ayteki̇n

2021

Decis. Mak. Appl. Manag. Eng.

View full text Add to dashboard Cite

show abstract

“…TOPSIS uses the principle that the chosen alternative must have the shortest distance from the ideal solution and furthest from the ideal solution from a geometric point of view by using the Euclidean distance to determine the relative proximity of an alternative with the optimal solution [2], [21], process TOPSIS as below: a. Build a normalized decision matrix b.…”

Section: Topsismentioning

confidence: 99%

Comparison Analysis of TOPSIS and Fuzzy Logic Methods On Fertilizer Selection

Indahingwati¹,

Wajdi²,

Susilo³

et al. 2018

IJET

View full text Add to dashboard Cite

Decision Support System is an interactive system that supports decision in the decision-making process through alternatives derived from the processing of data, information and design of the models. Selection decision support system of chemical fertilizer in fruit plant is expected to help anyone who wants to cultivate fruit trees can determine the chemical fertilizer as expected based alternatives and criteria set by the user. In this research method used is TOPSIS Method and Method of Fuzzy Logic. TOPSIS method is one of multiple criteria decision making method that uses the principle that the alternatives selected must have the shortest distance. Fuzzy Logic is a methodology of control systems troubleshooting, the fuzzy logic stated that everything is a binary which means it is only two possibilities, "Yes or No", "True or False", "Good or Bad", and others. Therefore, all of these can have a membership value of 0 or 1.

show abstract

“…They didn't consider LN in the study. Zadeh Sarraf et al [11] used statistical normalization for evaluating TOPSIS method in a more statistical situation.…”

Section: Introductionmentioning

confidence: 99%

A Vikor and Topsis Focused Reanalysis of the Madm Methods Based on Logarithmic Normalization

Zolfani

Yazdani²,

Pamučar³

et al. 2020

FU Mech Eng

View full text Add to dashboard Cite

Decision and policy-makers in multi-criteria decision-making analysis take into account some strategies in order to analyze outcomes and to finally make an effective and more precise decision. Among those strategies, the modification of the normalization process in the multiple-criteria decision-making algorithm is still a question due to the confrontation of many normalization tools. Normalization is the basic action in defining and solving a MADM problem and a MADM model. Normalization is the first, also necessary, step in solving, i.e. the application of a MADM method. It is a fact that the selection of normalization methods has a direct effect on the results. One of the latest normalization methods introduced is the Logarithmic Normalization (LN) method. This new method has a distinguished advantage, reflecting in that a sum of the normalized values of criteria always equals 1. This normalization method had never been applied in any MADM methods before. This research study is focused on the analysis of the classical MADM methods based on logarithmic normalization. VIKOR and TOPSIS, as the two famous MADM methods, were selected for this reanalysis research study. Two numerical examples were checked in both methods, based on both the classical and the novel ways based on the LN. The results indicate that there are differences between the two approaches. Eventually, a sensitivity analysis is also designed to illustrate the reliability of the final results.

show abstract

Developing TOPSIS method using statistical normalization for selecting knowledge management strategies

Cited by 36 publications

References 22 publications

Comparative Analysis of the Normalization Techniques in the Context of MCDM Problems

Comparative Analysis of the Normalization Techniques in the Context of MCDM Problems

Comparison Analysis of TOPSIS and Fuzzy Logic Methods On Fertilizer Selection

A Vikor and Topsis Focused Reanalysis of the Madm Methods Based on Logarithmic Normalization

Contact Info

Product

Resources

About