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 Comparing best-worst method and full consistency method in a fuzzy environment

2022 ◽  
Vol 11 (2) ◽  
pp. 181-192
Author(s):  
Arash Haqbin
Keyword(s):  
Decision Making ◽  
Real World ◽  
Pairwise Comparison ◽  
Multicriteria Decision Making ◽  
Fuzzy Environment ◽  
Study Results ◽  
Mcdm Method ◽  
Consistency Method ◽  
Best Worst Method

Multicriteria Decision Making (MCDM) is one the most important branches of decision theory. Due to the fact that MCDM methods have the utmost significance in management, scholars try to develop more MCDM methods. Since calculating the weights of criteria is an important step in any MCDM method, increasing the accuracy of weight calculating methods can highly affect these methods. This accuracy can be improved by less pairwise comparison between criteria. To this end, the present study seeks to make a comparison between two new weight calculating techniques, namely BWM and FUCOM in a fuzzy environment using a real-world case study Results of this study shows that FUCOM-F provides more reliable results compared to FBWM since its consistency is less than FBWM by a great amount.

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.

An Integrated Fuzzy Multi-Attribute Decision-Making Methodology for Evaluation of Mechanical Product

2010 ◽  
Vol 450 ◽  
pp. 534-538
Author(s):  
Yuan Chen ◽  
Bing Li ◽  
Xiao Jun Yang
Keyword(s):  
Decision Making ◽  
Fuzzy Topsis ◽  
Decision Makers ◽  
Weighting Method ◽  
Fuzzy Environment ◽  
Design Alternatives ◽  
Concept Evaluation ◽  
Criteria Weights ◽  
Multi Attribute Decision Making ◽  
Topsis Technique

The concept evaluation of mechanical product is essentially a multi-attribute decision making (MADM) problem in the fuzzy environment. In order to reduce the adverse impact of preference or judgments of decision makers on the final evaluation results, this paper attempts to propose an integrated fuzzy multi-attribute decision making methodology that combines the fuzzy TOPSIS technique and the objective weighting to evaluate mechanical product. The fuzzy TOPSIS technique is applied to rank the design alternatives, and the objective weighting method is integrated into the fuzzy TOPSIS technique to determine the appropriate criteria weights. Finally, a real application to pan mechanism selection for a cooking robot is demonstrated.

scholarly journals Multi-Criteria Decision Making Using TOPSIS Method Under Fuzzy Environment. Application in Spillway Selection

Proceedings ◽  
2018 ◽  
Vol 2 (11) ◽  
pp. 637 ◽  
Author(s):  
Vasiliki Balioti ◽  
Christos Tzimopoulos ◽  
Christos Evangelides
Keyword(s):  
Decision Making ◽  
Multiple Criteria Decision Making ◽  
Fuzzy Topsis ◽  
Topsis Method ◽  
Northern Greece ◽  
Analytic Hierarchy ◽  
Order Preference ◽  
Optimum Type ◽  
Topsis Technique ◽  
Selection Of

The selection of an appropriate spillway has a significant effect to the construction of a dam and several procedures and considerations are needed. In the past, this selection of the type of the spillway was arbitrary and sometimes with bad results. Recently the Multiple Criteria Decision Making theory has given the possibility to make a decision about the optimum form of a spillway under complex circumstances. In this paper, the above method is used and especially the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method for the selection of a spillway for a dam in the district of Kilkis in Northern Greece—‘Dam Pigi’. As the criteria were fuzzy and uncertain, the Fuzzy TOPSIS method is introduced together with the AHP (Analytic Hierarchy Process), which is used for the evaluation of criteria and weights. Five types of spillways were selected as alternatives and nine criteria. The criteria are expressed as triangular fuzzy numbers in order to formulate the problem. Finally, using the Fuzzy TOPSIS method, the alternatives were ranked and the optimum type of spillway was obtained.

scholarly journals A NOVEL FUZZY ENTROPY MEASURE AND ITS APPLICATION IN COVID-19 WITH FUZZY TOPSIS

2021 ◽  
Author(s):  
Razia Sharif
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Model Uncertainty ◽  
Multicriteria Decision Making ◽  
Fuzzy Topsis ◽  
Entropy Measure ◽  
Multicriteria Decision ◽  
Axiomatic Definition ◽  
Definition Of ◽  
Topsis Technique

Fuzzy sets (FSs) are an important tool to model uncertainty and vagueness. Entropy is being used to measure the fuzziness within a fuzzy set (FS). These entropies are used to find multicriteria decision-making. For measuring uncertainty with TOPSIS techniques an axiomatic definition of entropy measure for fuzzy sets is also given in this paper. The proposed entropy is provided to satisfy all the axioms. Several numerical examples are presented to compare the proposed entropy measure with existing entropies. The corresponding results show that the newly proposed entropy can be computed easily and give reliable results. Finally, the decision-making algorithm TOPSIS (Techniques of ordered preference similarity to ideal solution) is utilized to solve multicriteria decision-making problems (MCDM) related to daily life. In the current situation, COVID-19 has no proper medical treatment. We use TOPSIS technique to suggest an effective medicine for this pandemic. Numerical results and practical examples show the effectiveness and practical applicability of the proposed entropy.

scholarly journals INTEGRATED APPROACH OF FUZZY MULTI-ATTRIBUTE DECISION MAKING AND DATA MINING FOR CUSTOMER SEGMENTATION

2021 ◽  
Vol 24 (4) ◽  
pp. 174-188
Author(s):  
Manidatta Ray ◽  
Mamata Ray ◽  
Kamalakanta Muduli ◽  
Audrius Banaitis ◽  
Anil Kumar
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Fuzzy Ahp ◽  
Integrated Approach ◽  
Fuzzy Topsis ◽  
Ideal Solution ◽  
Fuzzy C Means ◽  
Order Preference ◽  
Multi Attribute Decision Making ◽  
Topsis Technique

This research work focuses on integrating the multi attribute decision making with data mining in a fuzzy decision environment for customer relationship management. The main objective is to analyse the relation between multi attribute decision making and data mining considering a complex problem of ordering customers segments, which is based on four criteria of customer’s life time value, viz. length (L), recency (R), frequency (F) and monetary value (M). The proposed integrated approach involves fuzzy C-means (FCM) cluster analysis as data mining tool. The experiment conducted using MATLAB 12.0 for identifying eight clusters of customers. The two multi attribute decision making tools i.e., fuzzy AHP (Analytic Hierarchy Process) and fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) are used for ranking these identified clusters. The applicability of the integrated decision making technique is also demonstrated in this paper considering the case of Indian retail sector. This research collected responses from nine experts from Indian retail industry regarding their perception of relative importance of four criteria of customer life value and evaluated weights of each criterion using fuzzy AHP. Transaction data of 18 months of the case retail store was analysed to segment 1,600 customers into eight clusters using fuzzy c-means clustering analysis technique. Finally, these eight clusters were ranked using fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Solution). The findings of this research could be helpful for firms in identifying the more valuable customers for them and allocate more resources to satisfy them. The findings will be also helpful in developing different loyalty program strategies for customers of different clusters.

scholarly journals The ILHWLAD-MCDM Framework for the Evaluation of Concrete Materials under an Intuitionistic Linguistic Fuzzy Environment

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Junjie Chen ◽  
Chonghui Zhang ◽  
Peipei Li ◽  
Mingxiao Xu
Keyword(s):  
Decision Making ◽  
Multicriteria Decision Making ◽  
Expanded Polystyrene ◽  
Energy Sustainability ◽  
Fuzzy Environment ◽  
Alternative Materials ◽  
Concrete Blocks ◽  
Concrete Materials ◽  
Selection Of

Concrete, one of the sources of energy consumption and carbon emissions, is widely used in the construction industry. The selection of concrete materials raises the question of energy sustainability and turns it into a complex multicriteria decision-making (MCDM) issue. To address this, we present an MCDM framework based on the intuitionistic linguistic hybrid weighted logarithmic averaging distance (ILHWLAD). To begin with, the intuitionistic linguistic numbers are used to deal with the uncertainty and fuzziness of the decision-making process. In addition, in view of the significance and the ordered position of the input arguments, an intuitionistic linguistic hybrid weighted logarithmic averaging distance (ILHWLAD) operator is defined. We, then, initiate the criteria system and present the MCDM framework based on the ILHWLAD to select the finest concrete. A case study involving four alternative materials, namely, autoclaved aerated concrete (AAC), hollow concrete blocks (HCB), expanded polystyrene (EPS), and lime hemp concrete (LHC), is presented to verify the scientificity of the framework.

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.

MULTIPLE CRITERIA CONSTRUCTION MANAGEMENT DECISIONS CONSIDERING RELATIONS BETWEEN CRITERIA / DAUGIATIKSLIAI STATYBOS VALDYMO SPRENDIMAI ATSIŽVELGIANT Į RODIKLIŲ TARPUSAVIO PRIKLAUSOMYBĘ

2010 ◽  
Vol 16 (1) ◽  
pp. 109-125 ◽  
Author(s):  
Jurgita Antuchevičienė ◽  
Edmundas Kazimieras Zavadskas ◽  
Algimantas Zakarevičius
Keyword(s):  
Decision Making ◽  
Mahalanobis Distance ◽  
Construction Management ◽  
Distance Measure ◽  
Multiple Criteria Decision Making ◽  
Multiple Criteria ◽  
Ideal Solution ◽  
Order Preference ◽  
Topsis Technique

Decision making in construction management has been always complicated especially if there were more than one criterion under consideration. Multiple criteria decision making (MCDM) has been often applied for complex decisions in construction when a lot of criteria were involved. Traditional MCDM methods, however, operate with independent and conflicting criteria. While in every day problems a decision maker often faces interactive and interrelated criteria. Accordingly, the need of improving and supplementing the methodology of compromise decisions arose. It was proposed to supplement TOPSIS (Technique for the Order Preference by Similarity to Ideal Solution) method and integrate the Mahalanobis distance in the usual algorythm of TOPSIS. Mahalanobis distance measure offered an option to take the correlations between the criteria into considerations while making the decision. A case study of building redevelopment in Lithuanian rural areas was presented that demonstrated the application of the proposed methodology. The case study proved that the proposed TOPSIS‐M (TOPSIS applying Mahalanobis distance measure) method could have substantial influence in carrying the proper decision. Santrauka Statybos valdymo spendimų priėmimas visuomet yra komplikuotas, ypač jei turime atsižvelgti į daugelį rodiklių. Kompleksiniams statybos sprendimams, kurie apibūdinami daugeliu rodiklių, taikomi daugiatiksliai sprendimų priėmimo metodai (MCDM ‐ Multiple Criteria Decision Making). Šie metodai skirti sprendimams priimti tuomet, kai vertinami konfliktuojantys bei nepriklausomi rodikliai. Tačiau realiose situacijose, priešingai, nuolat susiduriame su saveikaujančiais ir tarpusavio priklausomybę turinčiais rodikliais. Dėl šios priežasties kyla poreikis patobulinti sprendimų metodologiją. Straipsnyje siūloma papildyti variantų racionalumo nustatymo metoda TOPSIS (Technique for the Order Preference by Similarity to Ideal Solution), taikant Mahalanobio metoda atstumams nustatyti. Mahalanobio atstumų nustatymo metodas suteikia galimybę įvertinti koreliacinės rodiklių priklausomybės priimant daugiatikslį sprendimą. Siūlomos metodologijos taikymas įliustruojamas sprendžiant apleistų pastatų Lietuvos kaimo vietovėse racionalaus sutvarkymo uždavinį. Pateiktas pavyzdys patvirtina, kad TOPSIS‐M metodo (t. y. TOPSIS naudojant Mahalanobio atstuma) taikymas gali turėti esminę įtaka priimant sprendimą.

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

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