scholarly journals Sensitivity Analysis of the TOPSIS Method in Respect of Initial Data Distributions

2016 ◽  
Vol 55 (1) ◽  
pp. 45-51
Author(s):  
Rūta Simanavičienė ◽  
Vaida Petraitytė
Keyword(s):  
Decision Making ◽  
Sensitivity Analysis ◽  
Statistical Analysis ◽  
Initial Data ◽  
Beta Distribution ◽  
Probability Distributions ◽  
Data Distribution ◽  
Multiple Criteria Decision Making ◽  
Topsis Method ◽  
Log Normal

The present article investigates the sensitivity of the multiple criteria decision-making method TOPSIS in respectof attribute probability distributions. To carry out research, initial data – attribute values – were generated according to anormal, log-normal, uniform, and beta distributions. Decision matrixes were constructed from the generated data. Byapplying the TOPSIS method to the matrixes generated, result samples were received. A statistical analysis was conductedfor the results obtained, which revealed that the distributions of the initial data comply with the distributions of the resultsreceived by the TOPSIS method. According to the most common alternative rank value, it was ascertained that the TOPSISmethod is the most sensitive for data distribution according to beta distribution, and the least sensitive for data distributionaccording to lognormal distribution.

scholarly journals THE METHODS OF SENSITIVITY ANALYSIS AND THEIR USAGE FOR ANALYSIS OF MULTICRITERIA DECISION / JAUTRUMO ANALIZĖS METODAI IR JŲ NAUDOJIMAS DAUGIAKRITERINIAMS SPRENDIMAMS ANALIZUOTI

2011 ◽  
Vol 3 (1) ◽  
pp. 25-28 ◽  
Author(s):  
Rūta Simanavičienė ◽  
Leonas Ustinovičius
Keyword(s):  
Decision Making ◽  
Sensitivity Analysis ◽  
Initial Data ◽  
Multiple Criteria Decision Making ◽  
Multiple Criteria ◽  
Decision Making Process ◽  
Multicriteria Decision ◽  
Analysis Methods

In this paper we describe the application's fields of the sensitivity analysis methods. We pass in review the application of these methods in multiple criteria decision making, when the initial data are numbers. We formulate the problem, which of the sensitivity analysis methods is more effective for the usage in the decision making process.

scholarly journals Statistical Analysis of the Reliability of a Decision Obtained by the TOPSIS Method

2019 ◽  
Vol 54 (1) ◽  
pp. 110-118 ◽  
Author(s):  
Rūta Simanavičienė ◽  
Jovita Cibulskaitė
Keyword(s):  
Decision Making ◽  
Statistical Analysis ◽  
Initial Data ◽  
Confidence Intervals ◽  
Engineering Industry ◽  
Topsis Method ◽  
Multicriteria Decision ◽  
Data Errors ◽  
Measure Reliability ◽  
Statistical Analysis Methods

The tasks of making the most appropriate decisions taking into account a number of criteria are dealt with in variousfields such as engineering, industry, finance, economics and others. If the aim is to arrange the alternatives in a priority lineaccording to quantitative attributes, then multiattribute decision-making methods are suitable. Analysts using these methods usuallydo not take into account initial data errors – deviations in attribute values, in which case the decision may be unreliable. In thisarticle, several statistical analysis methods are proposed for the multicriteria decision to measure reliability: formulation of statisticalhypotheses and calculation of confidence intervals for parameters. Based on statistical analysis results, conclusions about thereliability of a multicriteria decision obtained using the TOPSIS method are formulated.

scholarly journals Multiple-Criteria Decision-Making and Sensitivity Analysis for Selection of Materials for Knee Implant Femoral Component

Materials ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2084
Author(s):  
Raman Kumar ◽  
Rohit Dubey ◽  
Sehijpal Singh ◽  
Sunpreet Singh ◽  
Chander Prakash ◽  
...  
Keyword(s):  
Decision Making ◽  
Sensitivity Analysis ◽  
Femoral Component ◽  
Human Life ◽  
Multiple Criteria Decision Making ◽  
Multiple Criteria ◽  
Biomedical Science ◽  
Human Beings ◽  
Weighted Sum Method ◽  
Selection Of

Total knee replacement (TKR) is a remarkable achievement in biomedical science that enhances human life. However, human beings still suffer from knee-joint-related problems such as aseptic loosening caused by excessive wear between articular surfaces, stress-shielding of the bone by prosthesis, and soft tissue development in the interface of bone and implant due to inappropriate selection of TKR material. The choice of most suitable materials for the femoral component of TKR is a critical decision; therefore, in this research paper, a hybrid multiple-criteria decision-making (MCDM) tactic is applied using the degree of membership (DoM) technique with a varied system, using the weighted sum method (WSM), the weighted product method (WPM), the weighted aggregated sum product assessment method (WASPAS), an evaluation based on distance from average solution (EDAS), and a technique for order of preference by similarity to ideal solution (TOPSIS). The weights of importance are assigned to different criteria by the equal weights method (EWM). Furthermore, sensitivity analysis is conducted to check the solidity of the projected tactic. The weights of importance are varied using the entropy weights technique (EWT) and the standard deviation method (SDM). The projected hybrid MCDM methodology is simple, reliable and valuable for a conflicting decision-making environment.

scholarly journals Complex T-spherical fuzzy Dombi aggregation operators and their applications in multiple-criteria decision-making

2021 ◽  
Author(s):  
Faruk Karaaslan ◽  
Mohammed Allaw Dawood Dawood
Keyword(s):  
Decision Making ◽  
Sensitivity Analysis ◽  
Fuzzy Set ◽  
Multiple Criteria Decision Making ◽  
Aggregation Operators ◽  
Multi Criteria Decision Making ◽  
Two Dimensional ◽  
Weighted Arithmetic ◽  
Mcdm Method ◽  
Dombi Operations

AbstractComplex fuzzy (CF) sets (CFSs) have a significant role in modelling the problems involving two-dimensional information. Recently, the extensions of CFSs have gained the attention of researchers studying decision-making methods. The complex T-spherical fuzzy set (CTSFS) is an extension of the CFSs introduced in the last times. In this paper, we introduce the Dombi operations on CTSFSs. Based on Dombi operators, we define some aggregation operators, including complex T-spherical Dombi fuzzy weighted arithmetic averaging (CTSDFWAA) operator, complex T-spherical Dombi fuzzy weighted geometric averaging (CTSDFWGA) operator, complex T-spherical Dombi fuzzy ordered weighted arithmetic averaging (CTSDFOWAA) operator, complex T-spherical Dombi fuzzy ordered weighted geometric averaging (CTSDFOWGA) operator, and we obtain some of their properties. In addition, we develop a multi-criteria decision-making (MCDM) method under the CTSF environment and present an algorithm for the proposed method. To show the process of the proposed method, we present an example related to diagnosing the COVID-19. Besides this, we present a sensitivity analysis to reveal the advantages and restrictions of our method.

Comparison Analysis of TOPSIS and Fuzzy Logic Methods On Fertilizer Selection

2018 ◽  
Vol 7 (2.3) ◽  
pp. 109 ◽  
Author(s):  
Asmara Indahingwati ◽  
Muh Barid Nizarudin Wajdi ◽  
Dwi Ermayanti Susilo ◽  
Nuning Kurniasih ◽  
Robbi Rahim
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Multiple Criteria Decision Making ◽  
Fruit Trees ◽  
Chemical Fertilizer ◽  
Interactive System ◽  
Topsis Method

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.  

scholarly journals Eliciting opinions of experts using uncertainty

2015 ◽  
Vol 56 ◽  
Author(s):  
Valentinas Podvezko ◽  
Askoldas Podviezko
Keyword(s):  
Decision Making ◽  
Probability Distribution ◽  
Decision Aid ◽  
Probability Distributions ◽  
Multiple Criteria Decision Making ◽  
Simulation Method ◽  
Statistical Simulation ◽  
Expert Evaluation ◽  
Absolute Level ◽  
Level Of Importance

Multiple criteria decision-making (MCDM) methods designed for evaluation of attractiveness of available alternatives, whenever used in decision-aid systems, imply active participation of experts. They participate in all stages of evaluation: casting a set of criteria, which should describe an evaluated process or an alternative; estimating level of importance of each criterion; estimating values of some criteria and sub-criteria. Social and economic processes are prone to laws of statistics,which are described and could be forecasted using the theory of probability. Weights of criteria, which reveal levels of their importance, could rarely be estimated with the absolute level of precision. Uncertainty of evaluation is characterised by a probability distribution. Aiming to elicit evaluation from experts we have to find either a distribution or a density function. Statistical simulation method can be used for estimation of evaluation of weights and/or values of criteria by experts. Alternatively, character of related uncertainty can be estimated by an expert himself during the survey process. The aim of this paper is to describe algorithms of expert evaluation with estimation of opinion uncertainty, which were applied in practice. In particular, a new algorithm was proposed, where an expert evaluates criteria by probability distributions.

scholarly journals Solving Civil Engineering Problems by Means of Fuzzy and Stochastic MCDM Methods: Current State and Future Research

2015 ◽  
Vol 2015 ◽  
pp. 1-16 ◽  
Author(s):  
Jurgita Antucheviciene ◽  
Zdeněk Kala ◽  
Mohamed Marzouk ◽  
Egidijus Rytas Vaidogas
Keyword(s):  
Decision Making ◽  
Sensitivity Analysis ◽  
Civil Engineering ◽  
Multiple Criteria Decision Making ◽  
Future Research ◽  
Building Information Modelling ◽  
Energy Efficient Buildings ◽  
Current State ◽  
Building Information ◽  
Methodological Problems

The present review examines decision-making methods developed for dealing with uncertainties and applied to solve problems of civil engineering. Several methodological difficulties emerging from uncertainty quantification in decision-making are identified. The review is focused on formal methods of multiple criteria decision-making (MCDM). Handling of uncertainty by means of fuzzy logic and probabilistic modelling is analysed in light of MCDM. A sensitivity analysis of MCDM problems with uncertainties is discussed. An application of stochastic MCDM methods to a design of safety critical objects of civil engineering is considered. Prospects of using MCDM under uncertainty in developing areas of civil engineering are discussed in brief. These areas are design of sustainable and energy efficient buildings, building information modelling, and assurance of security and safety of built property. It is stated that before long the decision-making in civil engineering may face several methodological problems: the need to combine fuzzy and probabilistic representations of uncertainties in one decision-making matrix, the necessity to extend a global sensitivity analysis to all input elements of a MCDM problem with uncertainties, and an application of MCDM methods in the areas of civil engineering where decision-making under uncertainty is presently not common.

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