Evaluation and ranking of insurance companies by combining TOPSIS and the interval fuzzy rough sets

Mimović, Predrag; Tadić, Danijela; Borota-Tišma, Ankica; Nestić, Snežana; Lafuente, Jaime Gil

doi:10.5937/sjm16-27672

Cited by 6 publications

(2 citation statements)

References 27 publications

(15 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Supplier Selection in Biofuel Companies based on Green criteria [26] R-BWM Supplier Selection in a Company Manufacturing PVC Carpentry Products [49] R-AHP, R-WASPAS Sustainable supplier selection [50] FUCOM, R-SAW Selection of railway wagons for the needs of internal transport [51] R-SWARA The risk assessment problem in a gas processing industry in Sfax (Tunisia) [52] IR-CODAS Evaluation of companies engaged in the transport of dangerous goods [53] IMF-SWARA, R-MARCOS Evaluation and ranking of insurance companies [54] IVFRNs-TOPSIS Offshore wind farm site selection [55] IRNs-BWM, MARCOS Selection of sustainable hydrogen production technology [56] rough-fuzzy BWM, DEA Sustainable supplier selection [57] intuitionistic linguistic rough MULTIMOORA Assessing sustainable production under circular economy context, a case of the forestry industry in the Eastern Black Sea region [58] Rough PIPRECIA, Fuzzy MARCOS Further, the description of rough numbers is provided according to [48,59]. Supposing that U is the universe containing all the objects, that Y is the limiting object of the universe U, and R is the set containing the elements (D 1 , D 2 , D 3 , .…”

Section: Application and Reference Methodsmentioning

confidence: 99%

Modification of the DIBR and MABAC Methods by Applying Rough Numbers and Its Application in Making Decisions

et al. 2022

View full text Add to dashboard Cite

This study considers the problem of selecting an anti-tank missile system (ATMS). The mentioned problem is solved by applying a hybrid multi-criteria decision-making model (MCDM) based on two methods: the DIBR (Defining Interrelationships Between Ranked criteria) and the MABAC (Multi-Attributive Border Approximation area Comparison) methods. The methods are modified by applying rough numbers, which present a very suitable area for considering uncertainty following decision-making processes. The DIBR method is a young method with a simple mathematical apparatus which is based on defining the relation between ranked criteria, that is, adjacent criteria, reducing the number of comparisons. This method defines weight coefficients of criteria, based on the opinion of experts. The MABAC method is used to select the best alternative from the set of the offered ones, based on the distance of the criteria function of every observed alternative from the border approximate area. The paper has two main innovations. With the presented decision-making support model, the ATMS selection problem is raised to a higher level, which is based on a proven mathematical apparatus. In terms of methodology, the main innovation is successful application of the rough DIBR method, which has not been treated in this way in the literature so far. Additionally, an analysis of the literature related to the research problem as well as to the methods used is carried out. After the application of the model, the sensitivity analysis of the output results of the presented model to the change of the weight coefficients of criteria is performed, as well as the comparison of the results of the presented model with other methods. Finally, the proposed model is concluded to be stable and multi-criteria decision-making methods can be a reliable tool to help decision makers in the selection process. The presented model has the potential of being applied in other case studies as it has proven to be a good means for considering uncertainty.

show abstract

Section: Application and Reference Methodsmentioning

confidence: 99%

Modification of the DIBR and MABAC Methods by Applying Rough Numbers and Its Application in Making Decisions

et al. 2022

View full text Add to dashboard Cite

show abstract

“…When evaluating the financial performance of economic entities in recent times, methods of multi-criteria analysis are increasingly used (Eyüboğlu and Çelik, 2016;Mandić et al, 2017;Lukić et al, 2020;Karadag et al, 2022, Lukić 2021Mimović et al, 2021;Gayathri et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

The assessment and ranking of the liquidity of Serbian agricultural enterprises

Sevkusic¹,

Bodiroga

Vukoje

2022

J AGR SCI BELGRADE

View full text Add to dashboard Cite

The key task of all enterprises, regardless of the activity they are engaged in, is constant growth and development. This is a prerequisite for survival in the modern market. The continuous monitoring and analysis of all production and financial performance of the enterprise are extremely important, with liquidity as the most important. It is a very important indicator of the overall financial condition of the company and is the most urgent requirement that is placed before modern companies. Liquidity is defined as the company's ability to timely settle its short-term liabilities. A comprehensive definition of liquidity implies that, in addition to the ability to settle short-term liabilities, the company has enough working capital to continue its current business activity. The focus of this research is on the financial performance of enterprises that, according to the official classification of activities, belong to sector A - Agriculture, forestry and fisheries. The aim of this paper is to evaluate the liquidity of these companies and perform the ranking by applying the modern method of multi-criteria decision-making MABAC. The results of the research clearly show that the liquidity of the agricultural sector of Serbia is not at a satisfactory level, and the best results were recorded in 2019.

show abstract

Design concept evaluation based on cloud rough model and modified AHP-VIKOR: An application to lithography tool manufacturing process

Sarwar,

Bashir

2024

Advanced Engineering Informatics

View full text Add to dashboard Cite

Evaluation and ranking of insurance companies by combining TOPSIS and the interval fuzzy rough sets

Cited by 6 publications

References 27 publications

Modification of the DIBR and MABAC Methods by Applying Rough Numbers and Its Application in Making Decisions

Modification of the DIBR and MABAC Methods by Applying Rough Numbers and Its Application in Making Decisions

The assessment and ranking of the liquidity of Serbian agricultural enterprises

Design concept evaluation based on cloud rough model and modified AHP-VIKOR: An application to lithography tool manufacturing process

Contact Info

Product

Resources

About