scholarly journals Daugiatikslių sprendimo priėmimo metodų jautrumo analizė taikant Monte Karlo modeliavimą

2011 ◽  
Vol 56 ◽  
pp. 182-190 ◽  
Author(s):  
Rūta Simanavičienė ◽  
Leonas Ustinovičius
Keyword(s):  
Decision Making ◽  
Sensitivity Analysis ◽  
Monte Carlo ◽  
Multicriteria Decision Making ◽  
Final Decision ◽  
Research Papers ◽  
Order Preference ◽  
Multicriteria Decisions ◽  
Simple Additive Weighting ◽  
Topsis Technique

Daugiakriteriams sprendimo priėmimo uždaviniams spręsti taikant kiekybinius daugiatikslius sprendimo priėmimo metodus, dažniausiai neatsižvelgiama į galimas pradinių duomenų – rodiklių reikšmių paklaidas. Todėl neaišku, ar gautas sprendimas (alternatyvų išrikiavimas pagal racionalumą) nesikeis, jeigu keistųsi rodiklių reikšmės (± n %, n< 50 %). Šiame straipsnyje, taikant Monte Karlo modeliavimą, atliekama kiekybinių daugiatikslių sprendimo priėmimo metodų – TOPISIS, SAW ir COPRAS – jautrumo analizė. Jautrumo analizės pagrindas yra rodiklių reikšmių pasiskirstymas. Darbo tikslas – sukurti jautrumo analizės modelį, kuriuo būtų galima nustatyti daugiatikslių metodų jautrumą rodiklių reikšmių pasiskirstymo dėsnio atžvilgiu ir įvertinti šiais metodais gauto sprendimo patikimumą. Pateikto jautrumo analizės modelio etapai: 1) rodiklių pseudoatsitiktinių reikšmių generavimas pagal tolygųjį ir normalųjį dėsnius; 2) alternatyvų racionalumų vertinimas nagrinėjamais metodais, naudojant generuotas sprendimų matricas; 3) metodų jautrumo ir gauto sprendimo patikimumo vertinimas. Modeliuojant sprendimo paramos sistemas, atliekant skaičiavimus sprendimo priėmimo metodais, rekomenduojama atsižvelgti į planuojamų taikyti metodų jautrumą, kad padidėtų sprendimo patikimumas.The Sensitivity Analysis of the Multiattribute Decision Making Methods by Monte Carlo SimulationRūta Simanavičienė, Leonas Ustinovičius SummaryThe quantitative multicriteria decision making methods are used for decision making, but the biases of the values of the attributes are ignored often. Therefore it is not clear, if the final decision were changed, when changing the values of attributes. There are scientific research papers intended for the sensitivity analysis of multicriteria decisions, according to the significances of attributes. This paper analyses the sensitivity of quantitative multiattribute decision making TOPSIS – Technique for Order Preference by Similarity to Ideal Solution, SAW – Simple Additive Weighting, COPRAS – COmplex PRoportional ASsessment methods, according to attribute distribution. On this basis of Monte Carlo modeling (simulation) the generation of pseudorandom attribute values is being made, according to uniform and normal distribution. Using generated data the efficiency of alternatives is carried out by the above methods. As a result the sensitivity of the methods and the reliability of final decision are presented. When multiattribute decision making methods are used on the modeling decision support systems it is recommended to consider the sensitivity of these methods.

scholarly journals Evaluation of a Third-Party Logistics (3PL) Provider Using a Rough SWARA–WASPAS Model Based on a New Rough Dombi Agregator

Symmetry ◽  
2018 ◽  
Vol 10 (8) ◽  
pp. 305 ◽  
Author(s):  
Siniša Sremac ◽  
Željko Stević ◽  
Dragan Pamučar ◽  
Miloš Arsić ◽  
Bojan Matić
Keyword(s):  
Decision Making ◽  
Sensitivity Analysis ◽  
Third Party ◽  
Third Party Logistics ◽  
Dangerous Goods ◽  
Supply Chain Logistics ◽  
Transport Services ◽  
Simple Additive Weighting ◽  
Transport Of Dangerous Goods ◽  
Topsis Technique

For companies active in various sectors, the implementation of transport services and other logistics activities has become one of the key factors of efficiency in the total supply chain. Logistics outsourcing is becoming more and more important, and there is an increasing number of third party logistics providers. In this paper, logistics providers were evaluated using the Rough SWARA (Step-Wise Weight Assessment Ratio Analysis) and Rough WASPAS (Weighted Aggregated Sum Product Assessment) models. The significance of the eight criteria on the basis of which evaluation was carried out was determined using the Rough SWARA method. In order to allow for a more precise consensus in group decision-making, the Rough Dombi aggregator was developed in order to determine the initial rough matrix of multi-criteria decision-making. A total of 10 logistics providers dealing with the transport of dangerous goods for chemical industry companies were evaluated using the Rough WASPAS approach. The obtained results demonstrate that the first logistics provider is also the best one, a conclusion confirmed by a sensitivity analysis comprised of three parts. In the first part, parameter ρ was altered through 10 scenarios in which only alternatives four and five change their ranks. In the second part of the sensitivity analysis, a calculation was performed using the following approaches: Rough SAW (Simple Additive Weighting), Rough EDAS (Evaluation Based on Distance from Average Solution), Rough MABAC (MultiAttributive Border Approximation Area Comparison), and Rough TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution). They showed a high correlation of ranks determined by applying Spearman’s correlation coefficient in the third part of the sensitivity analysis.

scholarly journals A COMPARISON OF FUZZY MULTICRITERIA DECISION MAKING METHODS FOR INTELLIGENT BUILDING ASSESSMENT

2014 ◽  
Vol 20 (1) ◽  
pp. 59-69 ◽  
Author(s):  
İhsan Kaya ◽  
Cengiz Kahraman
Keyword(s):  
Decision Making ◽  
Multicriteria Decision Making ◽  
Building Design ◽  
Intelligent Building ◽  
Analytic Hierarchy ◽  
Multicriteria Decision ◽  
Intelligent Buildings ◽  
Building Assessment ◽  
Order Preference ◽  
Topsis Technique

The methodology, Multicriteria Decision Making (MCDM), refers to finding the best alternative from all of the feasible alternatives in the presence of multiple, usually conflicting, decision criteria. Nowadays, intelligent buildings’ performance that is increasingly evidenced in building design and construction has been analyzed by using MCDM techniques. Intelligent buildings (IBs) are also under assessment according to their IB related characteristics and actual circumstances as a MCDM problem. In this paper, two most known MCDM methodologies, Analytic Hierarchy Process (AHP) and TOPSIS (Technique for Order Preference by Similarity to Ideal Solution), are used for intelligent building assessment under fuzzy environment for dealing with the evaluations’ uncertainty and imprecision in which the expert's comparisons that are represented as fuzzy numbers. For this aim, three intelligent building alternatives for a business centre in Istanbul are evaluated by using these two fuzzy MCDM methods and the obtained ranking results are compared.

scholarly journals A NEW SYNTHESIS METHOD OF STRUCTURAL, TECHNOLOGICAL AND SAFETY DECISIONS (SYMAD-3) / NAUJAS KONSTRUKCINIŲ, TECHNOLOGINIŲ IR SAUGOS SPRENDIMŲ SINTEZĖS METODAS (SYMAD-3)

2012 ◽  
Vol 18 (2) ◽  
pp. 265-276 ◽  
Author(s):  
Ruta Simanaviciene ◽  
Rita Liaudanskiene ◽  
Leonas Ustinovichius
Keyword(s):  
Decision Making ◽  
Synthesis Method ◽  
Multiple Attribute Decision Making ◽  
Ideal Solution ◽  
Quantitative Measurements ◽  
New Synthesis ◽  
Multiple Attribute ◽  
Order Preference ◽  
Simple Additive Weighting ◽  
Topsis Technique

The paper provides a new synthesis method of multiple attribute decisions (SyMAD-3 – Synthesis of Multiple Attribute Decisions using three methods) intended for combining multi-stage and multiple attribute decisions into a single common estimate. The method is applied for selecting a construction project on the basis of its structural, technological and safety decisions. To increase the reliability of the decision, three multiple attribute decision-making methods based on quantitative measurements were applied to help the person making a decision to monitor the results of a relevant decision obtained employing three methods of the same class. The algorithm of the proposed method includes methods for identifying the integrated significances of attributes and multiple attribute decision-making methods (SAW – Simple Additive Weighting, TOPSIS – Technique for Order Preference by Similarity to Ideal Solution, and COPRAS – COmplex PRoportional ASsessment) based on quantitative measurements. Santrauka Šiame darbe autoriai pateikia naują daugiakriterinių sprendimų sintezės metodą (SyMAD-3 – Synthesis of Multiple Attribute Decisions using three methods), skirtą daugiapakopiams, daugiatiksliams sprendimams apjungti į vieną bendrą įvertį. Metodas taikomas statybos projektui parinkti atsižvelgiant į konstrukcinius, technologinius ir saugos sprendimus. Sprendimo patikimumui padidinti taikomi trys kiekybiniais matavimais pagrįsti daugiatiksliai sprendimo priėmimo metodai, kuriais remdamasis sprendimą priimantis asmuo gali stebėti jam aktualaus sprendimo rezultatus, gautus trimis metodais, priklausančiais tai pačiai klasei. Pateikto metodo algoritme taikomi efektyvumo rodiklių integruoto reikšmingumo nustatymo ir daugiatiksliai sprendimo priėmimo (SAW – Simple Additive Weighting, TOPSIS – Technique for Order Preference by Similarity to Ideal Solution, COPRAS – COmplex PRoportional ASsessment) metodai, pagrįsti kiekybiniais matavimais.

scholarly journals SIMILARITY BASED FUZZY INFERIOR RATIO FOR SOLVING MULTICRITERIA DECISION MAKING PROBLEMS

2020 ◽  
Vol 5 (2) ◽  
pp. 597
Author(s):  
Sharifah Aniza Sayed Ahmad ◽  
Daud Mohamad ◽  
Nurul Iffah Azman
Keyword(s):  
Decision Making ◽  
Similarity Measure ◽  
Multicriteria Decision Making ◽  
Fuzzy Topsis ◽  
Compromise Solution ◽  
Fuzzy Environment ◽  
Order Preference ◽  
Topsis Technique ◽  
Distance Approach

The method of Fuzzy Inferior Ratio (FIR) has been recognized as one of advantageous methods in multi criteria decision-making under fuzzy environment as it considers the element of compromise solution between the positive and negative aspect of the evaluation simultaneously. It is considered as an improvised version of Fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method for solving decision-making problems. However, the FIR utilizes the distance approach in the evaluation in obtaining the compromise solution. A defuzzification process is carried out to transform the fuzzy values into a crisp form. Hence, loss of information may occur in the computation. In this paper, we proposed a similarity-based FIR in order to overcome the above-mentioned problem. A new compromise solution for the proposed FIR is developed and an improvised procedure of FIR is suggested using the similarity measure approach. A comparative analysis between the distance based and the similarity-based FIR is carried out using a case study of preferred client selection for a loan application. The proposed method is found to be effective in solving decision-making problems as the utilization of similarity measure will sufficiently preserve the data information in the computational process of evaluation.  

scholarly journals Selecting the savings account in the Slovak Republic

2016 ◽  
Vol 14 (4) ◽  
pp. 8-16 ◽  
Author(s):  
Marek Mehea ◽  
Slavomíra Staaková ◽  
Adela Feranecová ◽  
Veronika Ragániová
Keyword(s):  
Decision Making ◽  
Slovak Republic ◽  
Multicriteria Decision Making ◽  
Jel Classification ◽  
Multicriteria Decision ◽  
Savings Accounts ◽  
Order Preference ◽  
Mutual Comparison ◽  
High Yields ◽  
Topsis Technique

There are currently many investment and financial products that can be used for capitalizing of savings. Although investments in various commodities, shares, securities, or funds can be with high yields, it requires some knowledge and experience. Unattempted investor may experience unpleasant surprise of possible losses of greater amount of money, as such investments are generally associated with a higher risk. For these reasons, the majority of the population remains in the Slovak Republic faithful to traditional forms of capitalizing of funds. One of these forms are savings accounts in banks. The main purpose of this paper is to find possibly the best savings account in the Slovak Republic. In cooperation with experts from the field of banking, the authors have defined the selection criteria of savings accounts, assessed their importance and, then, they have arranged savings accounts offered in the Slovak Republic according to achieved score. For this purpose, methods of multicriteria decision making were used. These methods are based on the evaluation of several alternative solutions based on multiple criteria. These criteria must be assigned by weights which represent their importance in decision making process. These weights were calculated using the Saaty’s method, which is a method based on mutual comparison of all the criteria. For final ranking of term deposits, taking into account the weights of the criteria, the method TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) was used. Keywords: savings, banking products, savings accounts, multicriteria decision making. JEL Classification: E21, G21

scholarly journals A Decision-Making Approach Based on TOPSIS Method for Ranking Smart Cities in the Context of Urban Energy

Energies ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 2691
Author(s):  
Sławomira Hajduk ◽  
Dorota Jelonek
Keyword(s):  
Decision Making ◽  
Smart Cities ◽  
Energy Performance ◽  
Linear Ordering ◽  
Topsis Method ◽  
Research Papers ◽  
The World ◽  
Urban Energy ◽  
World Council ◽  
Topsis Technique

This paper presents the use of multi-criteria decision-making (MCDM) for the evaluation of smart cities. During the development of the method, the importance of the decision-making approach in the linear ordering of cities was presented. The method of using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) was proposed for the preparation of ranking. The method was verified by the application in the measurement of energy performance in smart cities. The authors conducted a literature review of research papers related to urban energy and MCDM published in the period from 2010 to 2020. The paper uses data from the World Council on City Data (WCCD). The research conducted allowed for the identification of the most popular MCDM techniques in the field of urban energy such as TOPSIS, AHP and DEA. The TOPSIS technique was used to organize and group the analyzed cities. Porto took the top position, whereas Buenos Aries was the last.

scholarly journals Sistem Pendukung Keputusan Pemberian Reward Pegawai Menggunakan Metode TOPSIS

2020 ◽  
Vol 18 (1) ◽  
pp. 11
Author(s):  
Aisyah Mutia Dawis
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Selection Process ◽  
Multiple Attribute Decision Making ◽  
Management Problem ◽  
Multiple Attribute ◽  
Ideal Solutions ◽  
Order Preference ◽  
Topsis Technique ◽  
A Company

Every company has management providing wages or rewards to employees. This is because employees are one of the resources that are used as a driving force in advancing a company. Besides, many companies provide rewards to their employees with the aim of motivating employees to help more. There is management problem in PKU Muhammadiyah Gamping Hospital for determining the number of rewards obtained by employees because many variables are determined. Therefore, the need of management information system can facilitate the Management of the PKU Muhammadiyah Gamping Hospital in determining decision making for providing rewards. One method that is often used in implementing decision support systems is Multiple Attribute Decision Making (MADM), focusing TOPSIS (Technique for Order Preference with Similarities to Ideal Solutions). By the implementation of the decision support system, PKU Muhammadiyah Gamping Hospital can carry out the selection process more efficiently.The test results by matching the employee data results at PKU Muhammadiyah Hospital obtained 95.83% accuracy so that this system can help the PKU Muhammadiyah Hospital in determining employee rewards.

scholarly journals Enterprise Credit Risk Management Using Multicriteria Decision-Making

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Wenjuan Liu
Keyword(s):  
Decision Making ◽  
Risk Management ◽  
Credit Risk ◽  
Multicriteria Decision Making ◽  
Final Decision ◽  
Credit Risk Management ◽  
Multicriteria Decision ◽  
Risk Manager ◽  
Enterprise Credit ◽  
Weight Calculation

The purpose of this study is to reduce the rate of multicriteria decision-making (MCDA) errors in credit risk management and to weaken the influence of different attitudes of enterprise managers on the final decision when facing credit risk. First, several solutions that are suitable for present enterprise credit risk management are proposed according to the research of enterprise risk management in the world. Moreover, the criteria and matrix are established according to the general practice of the expert method. A decision-making method of enterprise credit risk management with trapezoidal fuzzy number as the criteria of credit risk management is proposed based on the prospect theory; then, the weight is calculated based on G1 weight calculation, G2 weight calculation method, and the method of maximizing deviation; finally, the prospect values of the alternatives calculated by each method are adopted to sort and compare the proposed solutions. Considering the difference of risk degree of managers in the face of credit risk management, the ranking results of enterprise credit risk management solutions based on three weight calculation methods are compared. The results show that as long as the quantitative value of the risk attitude of the enterprise credit risk manager meets a certain range, the final choice of credit risk management scheme ranking is consistent. This exploration provides a new research direction for enterprise credit risk management, which has reference significance.

Disentangling uncertainties in risk-based planning of water resources in the UK

2021 ◽  
Author(s):  
Francesca Pianosi ◽  
Andres Penuela-Fernandez ◽  
Christopher Hutton
Keyword(s):  
Decision Making ◽  
Sensitivity Analysis ◽  
Monte Carlo ◽  
Water Resources ◽  
Water Resources Planning ◽  
Adaptive Planning ◽  
Water Companies ◽  
The Uk ◽  
Resources Planning

&lt;p&gt;Proper consideration of uncertainty has become a cornerstone of model-informed planning of water resource systems. In the UK Government&amp;#8217;s 2020 Water Resources Planning Guidelines, the word &amp;#8220;uncertainty&amp;#8221; appears 48 times in 82 pages. This emphasis on uncertainty aligns with the increasing adoption by UK water companies of a &amp;#8220;risk-based&amp;#8221; approach to their long-term decision-making, in order to handle uncertainties in supply-demand estimation, climate change, population growth, etc. The term &amp;#8220;risk-based&amp;#8221; covers a range of methods - such as &amp;#8220;info-gap&amp;#8221;, &amp;#8220;robust decision-making&amp;#8221; or &amp;#8220;system sensitivity analysis&amp;#8221; - that come under different names but largely share a common rationale, essentially based on the use of Monte Carlo simulation. This shift in thinking from previous (deterministic) &amp;#8220;worst-case&amp;#8221; approach to a &amp;#8220;risk-based&amp;#8221; one is important and has the potential to significantly improve water resources planning practice. However its implementation is diminished by a certain lack of clarity about the terminology in use and about the concrete differences (and similarities) among methods. On top of these difficulties, in the next planning-cycle (2021-2026) two further step changes are introduced: (1) water companies are requested to move from a cost-efficiency approach focused on achieving the supply-demand balance, towards a fully multi-criteria approach that more explicitly encompasses other objectives including environmental sustainability; (2) as a further way to handle long-term uncertainties, they are required to embrace an &amp;#8220;adaptive planning&amp;#8221; approach. These changes will introduce two new sets of uncertainties around the robust quantification of criteria, particularly environmental ones, and around the attribution of weights to different criteria. This urgently calls for establishing structured approaches to quantify not only the uncertainty in model outputs, but also the sensitivity of those outputs to different forms of uncertainty in the modelling chain that mostly control the variability of the final outcome &amp;#8211; the &amp;#8220;best value&amp;#8221; plan. Without this understanding of critical uncertainties, the risk is that huge efforts are invested on characterising and/or reducing uncertainties that later turn out to have little impact on the final outcome; or that water managers fall back to using oversimplified representation of those uncertainties as a way to escape the huge modelling burden. In this work, we aim at starting to establish a common rationale to &amp;#8220;risk-based&amp;#8221; methods within the context of a fully multi-criteria approach. We use a proof-of-concept example of a reservoir system in the South-West of England to demonstrate the use of global (i.e. Monte Carlo based) sensitivity analysis to simultaneously quantify output uncertainty and sensitivity, and identify robust decisions. We also discuss the potential of this approach to inform the construction of a &amp;#8220;decision tree&amp;#8221; for adaptive planning.&lt;/p&gt;

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