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 A New Grey Approach for Using SWARA and PIPRECIA Methods in a Group Decision-Making Environment

Mathematics ◽  
2021 ◽  
Vol 9 (13) ◽  
pp. 1554
Author(s):  
Dragiša Stanujkić ◽  
Darjan Karabašević ◽  
Gabrijela Popović ◽  
Predrag S. Stanimirović ◽  
Muzafer Saračević ◽  
...  
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Multiple Criteria Decision Making ◽  
Grey System Theory ◽  
Multiple Criteria ◽  
Decision Making Process ◽  
Grey System ◽  
Criteria Weights

The environment in which the decision-making process takes place is often characterized by uncertainty and vagueness and, because of that, sometimes it is very hard to express the criteria weights with crisp numbers. Therefore, the application of the Grey System Theory, i.e., grey numbers, in this case, is very convenient when it comes to determination of the criteria weights with partially known information. Besides, the criteria weights have a significant role in the multiple criteria decision-making process. Many ordinary multiple criteria decision-making methods are adapted for using grey numbers, and this is the case in this article as well. A new grey extension of the certain multiple criteria decision-making methods for the determination of the criteria weights is proposed. Therefore, the article aims to propose a new extension of the Step-wise Weight Assessment Ratio Analysis (SWARA) and PIvot Pairwise Relative Criteria Importance Assessment (PIPRECIA) methods adapted for group decision-making. In the proposed approach, attitudes of decision-makers are transformed into grey group attitudes, which allows taking advantage of the benefit that grey numbers provide over crisp numbers. The main advantage of the proposed approach in relation to the use of crisp numbers is the ability to conduct different analyses, i.e., considering different scenarios, such as pessimistic, optimistic, and so on. By varying the value of the whitening coefficient, different weights of the criteria can be obtained, and it should be emphasized that this approach gives the same weights as in the case of crisp numbers when the whitening coefficient has a value of 0.5. In addition, in this approach, the grey number was formed based on the median value of collected responses because it better maintains the deviation from the normal distribution of the collected responses. The application of the proposed approach was considered through two numerical illustrations, based on which appropriate conclusions were drawn.

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 Systematic Approach for the selection of monitoring technologies in CO2 geological storage projects. Application of multicriteria decision making

2013 ◽  
Vol 16 (1) ◽  
pp. 36-42
Keyword(s):  
Decision Making ◽  
Co2 Storage ◽  
Multiple Criteria Decision Making ◽  
Multicriteria Decision Making ◽  
Multiple Criteria ◽  
Simultaneous Optimization ◽  
Case Scenario ◽  
Multicriteria Decision ◽  
Measurement Monitoring ◽  
Selection Of

<p>Geologic storage of carbon dioxide (CO2) has been proposed as a viable means for reducing anthropogenic CO2 emissions. Once injection begins, a program for measurement, monitoring, and verification (MMV) of CO2 distribution is required in order to: a) research key features, effects and processes needed for risk assessment; b) manage the injection process; c) delineate and identify leakage risk and surface escape; d) provide early warnings of failure near the reservoir; and f) verify storage for accounting and crediting. The selection of the methodology of monitoring (characterization of site and control and verification in the post-injection phase) is influenced by economic and technological variables. Multiple Criteria Decision Making (MCDM) refers to a methodology developed for making decisions in the presence of multiple criteria. MCDM as a discipline has only a relatively short history of 40 years, and it has been closely related to advancements on computer technology. Evaluation methods and multicriteria decisions include the selection of a set of feasible alternatives, the simultaneous optimization of several objective functions, and a decision-making process and evaluation procedures that must be rational and consistent. The application of a mathematical model of decision-making will help to find the best solution, establishing the mechanisms to facilitate the management of information generated by number of disciplines of knowledge. Those problems in which decision alternatives are finite are called Discrete Multicriteria Decision problems. Such problems are most common in reality and this case scenario will be applied in solving the problem of site selection for storing CO2. Discrete MCDM is used to assess and decide on issues that by nature or design support a finite number of alternative solutions. Recently, Multicriteria Decision Analysis has been applied to hierarchy policy incentives for CCS, to assess the role of CCS, and to select potential areas which could be suitable to store. For those reasons, MCDM have been considered in the monitoring phase of CO2 storage, in order to select suitable technologies which could be techno-economical viable. In this paper, we identify techniques of gas measurements in subsurface which are currently applying in the phase of characterization (pre-injection); MCDM will help decision-makers to hierarchy the most suitable technique which fit the purpose to monitor the specific physic-chemical parameter.</p>

scholarly journals Announcing the 26th International Conference on Multicriteria Decision-making

2021 ◽  
Vol 13 (3) ◽  
Author(s):  
Enrique Mu
Keyword(s):  
Decision Making ◽  
Research Abstract ◽  
Multiple Criteria Decision Making ◽  
Multicriteria Decision Making ◽  
Multiple Criteria ◽  
Multicriteria Decision ◽  
International Conference ◽  
Submission Deadline ◽  
The University

We are very pleased to announce that the 26th International Conference on Multiple Criteria Decision Making will be held at the University of Portsmouth from June 26 - July 1, 2022. There will be an AHP/ANP track co-chaired by Enrique Mu and Rozann Saaty which will be sponsored, as in previous years, by the Creative Decisions Foundation. This is an opportunity for AHP/ANP scholars to submit their research. Abstract submissions (with a maximum of 600 characters) will be opened in early December with a submission deadline of March 1, 2022.

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.

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