Прегледај по Аутор "Kumar Das, Dillip"
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- СтавкаA New Fuzzy MARCOS Method for Road Tra c Risk Analysis(MDPI, 2020) Stanković, Miomir; Stević, Željko; Kumar Das, Dillip; Subotić, Marko; Pamučar, DraganIn this paper, a new fuzzy multi-criteria decision-making model for tra c risk assessment was developed. A part of a main road network of 7.4 km with a total of 38 Sections was analyzed with the aim of determining the degree of risk on them. For that purpose, a fuzzy Measurement Alternatives and Ranking according to the COmpromise Solution (fuzzy MARCOS) method was developed. In addition, a new fuzzy linguistic scale quantified into triangular fuzzy numbers (TFNs) was developed. The fuzzy PIvot Pairwise RElative Criteria Importance Assessment—fuzzy PIPRECIA method—was used to determine the criteria weights on the basis of which the road network sections were evaluated. The results clearly show that there is a dominant section with the highest risk for all road participants, which requires corrective actions. In order to validate the results, a comprehensive validity test was created consisting of variations in the significance of model input parameters, testing the influence of dynamic factors—of reverse rank, and applying the fuzzy Simple Additive Weighing (fuzzy SAW) method and the fuzzy Technique for Order of Preference by Similarity to Ideal Solution (fuzzy TOPSIS). The validation test show the stability of the results obtained and the justification for the development of the proposed model.
- СтавкаA New Hybrid MCDM Model: Sustainable Supplier Selection in a Construction Company(MDPI, 2019) Matić, Bojan; Jovanović, Stanislav; Kumar Das, Dillip; Kazimieras Zavadskas, Edmundas; Stević, Željko; Sremac, Siniša; Marinković, MilanSustainable development is one of the most important preconditions for preserving resources and balanced functioning of a complete supply chain in different areas. Taking into account the complexity of sustainable development and a supply chain, different decisions have to be made day-to-day, requiring the consideration of different parameters. One of the most important decisions in a sustainable supply chain is the selection of a sustainable supplier and, often the applied methodology is multi-criteria decision-making (MCDM). In this paper, a new hybrid MCDM model for evaluating and selecting suppliers in a sustainable supply chain for a construction company has been developed. The evaluation and selection of suppliers have been carried out on the basis of 21 criteria that belong to all aspects of sustainability. The determination of the weight values of criteria has been performed applying the full consistency method (FUCOM), while a new rough complex proportional assessment (COPRAS) method has been developed to evaluate the alternatives. The rough Dombi aggregator has been used for averaging in group decision-making while evaluating the significance of criteria and assessing the alternatives. The obtained results have been checked and confirmed using a sensitivity analysis that implies a four-phase procedure. In the first phase, the change of criteria weight was performed, while, in the second phase, rough additive ratio assessment (ARAS), rough weighted aggregated sum product assessment (WASPAS), rough simple additive weighting (SAW), and rough multi-attributive border approximation area comparison (MABAC) have been applied. The third phase involves changing the parameter r in the modeling of rough Dombi aggregator, and the fourth phase includes the calculation of Spearman’s correlation coefficient (SCC) that shows a high correlation of ranks.
- СтавкаA Novel Data-Envelopment Analysis Interval-Valued Fuzzy-Rough-Number Multi-Criteria Decision-Making (DEA-IFRN MCDM) Model for Determining the Efficiency of Road Sections Based on Headway Analysis(MDPI, 2024) Andjelković, Dejan; Stojić, Gordan; Nikolić, Nikola; Kumar Das, Dillip; Subotić, Marko; Stević, ŽeljkoThe capacity of transport infrastructure is one of the very important tasks in transport engineering, which depends mostly on the geometric characteristics of road and headway analysis. In this paper, we have considered 14 road sections and determined their efficiency based on headway analysis. We have developed a novel interval fuzzy-rough-number decision-making model consisting of DEA (data envelopment analysis), IFRN SWARA (interval-valued fuzzy-rough-number stepwise weight-assessment-ratio analysis), and IFRNWASPAS (interval-valued fuzzy-rough-number weighted-aggregate sum–product assessment) methods. The main contribution of this study is a new extension of WASPAS method with interval fuzzy rough numbers. Firstly, the DEA model was applied to determine the efficiency of 14 road sections according to seven input–output parameters. Seven out of the fourteen alternatives showed full efficiency and were implemented further in the model. After that, the IFRN SWARA method was used for the calculation of the final weights, while IFRNWASPAS was applied for ranking seven of the road sections. The results show that two sections are very similar and have almost equal efficiency, while the other results are very stable. According to the results obtained, the best-ranked is a measuring segment of the Ivanjska–Šargovac section, with a road gradient = 5.5%, which has low deviating values of headways according to the measurement classes from PC-PC to AT-PC, which shows balanced and continuous traffic flow. Finally, verification tests such as changing the criteria weights, comparative analysis, changing the parameter, and reverse rank analysis have been performed.
- СтавкаA Novel Integrated Interval Rough MCDM Model for Ranking and Selection of Asphalt Production Plants(MDPI, 2021) Matić, Bojan; Jovanović, Stanislav; Marinković, Milan; Sremac, Siniša; Kumar Das, Dillip; Stević, ŽeljkoAsphalt production plants play an important role in the field of civil engineering, but also in the entire economic system since the construction of roads enables uninterrupted functioning within it. In this paper, the ranking of asphalt production plants on the territory of the Autonomous Province of Vojvodina has been performed. The modern economy needs contemporary models and methods to solve complicated MCDM problems and, for these purposes, it has been developed an original Interval Rough Number (IRN) Multi-criteria decision-making (MCDM) model that implies an extension of two methods belonging to the field with interval rough numbers. After forming a list of eight most significant criteria for assessing the efficiency of asphalt production plants, the Interval Rough Number PIvot Pairwise RElative Criteria Importance Assessment (IRN PIPRECIA) method was developed to determine the significance of the criteria. A total of 21 locations with asphalt mixture installation were considered. For that purpose, seven asphalt production plants were included, and for their ranking, the IRN EDAS (Evaluation based on Distance from Average Solution) method was created. The aim of this paper is to develop a novel interval rough model that can be useful for determining the efficiency of asphalt production plants. Averaging in group decision-making (GDM) for both methods was performed using an IRN Dombi weighted geometric averaging (IRNDWGA) aggregator. The obtained results show that (A15) Ruma (SP)–Mačvanska Mitrovica–Zasavica has the best characteristics out of the set of locations considered in this study. However, Alternatives A6 and A19 are also variants with remarkably good characteristics since there is very little difference in values compared to the first-ranked alternative. Also, the obtained results have shown that the developed model is applicable, which is proven through a comparative analysis
- СтавкаA novel interval rough model for optimizing road network performance and safety(ELSEVIER, 2024) Na, Zhou; Stević, Željko; Subotić, Marko; Kumar Das, Dillip; Kou, Gang; Moslem, SarbastThis paper introduces a novel Integrated Interval Rough Pivot Pairwise Relative Criteria Importance Assessment (IRN PIPRECIA) model combined with Interval Rough Combined Compromise Solution (IRN CoCoSo), marking a significant advancement in sustainable traffic flow management for commercial vehicles. This innovative merger is a first in literature, methodologically enhancing the evaluation of road sections based on critical parameters including passenger car equivalent (PCE) 85%, AADT, road conditions, and accident data. Our model systematically fills the research gap in holistic traffic performance analysis, providing a unique tool for prioritizing road safety and efficiency. The key scientific contribution is the model’s ability to integrate causal and consequential traffic factors into a single framework, offering a novel multi-criteria decision-making (MCDM) approach. Results, validated through various verification models, show the integrated model’s effectiveness in real-world scenarios, confirming its robustness and stability. With strong engineering application potential, our work supports urban planners and traffic managers in making informed, sustainable decisions. The model extends beyond traditional traffic analysis, promising a shift towards more adaptive, data-driven infrastructure management. Future research will aim to refine the criteria basis and explore real-time decision-making through advanced MCDM applications.
- СтавкаA Novel Multiphase Model for Traffic Safety Evaluation: A Case Study of South Africa(Hindawi, 2021) Stević, Željko; Kumar Das, Dillip; Kopić, MilošIdentification of key indicators that cause safety challenges and vulnerable roads is crucial for improving traffic safety. This paper, therefore, entails to the development of a novel multiphase multicriteria decision-making (MCDM) model to evaluate the vulnerability of urban roads for traffic safety. This was conducted by using data from 17 important roads of a South African city and combining several methods such as CRiteria Importance through Intercriteria Correlation (CRITIC), data envelopment analysis (DEA), and measurement of alternatives and ranking according to compromise solution (MARCOS). Taking the elements of the DEA method, two new approaches for calculating the weights of criteria, the DEA-1 and DEA-2 models, were formed and integrated with the CRITIC method to obtain the final values of criteria weights. The MARCOS method was applied to evaluate 17 alternatives, for each direction separately. The aim of developing such a model is to use the advantages of obtaining objectivity of criteria weights through linear programming and correlation of values of the collected data. Also, the MARCOS method, as one of the newer and applicable methods, provides additional significance. Extensive sensitivity analyses were conducted to validate the model. The findings suggest that there are a certain number of roads that have a high level of safety for both directions, as well as a group of risky roads, which need traffic improvement measures. Thus, the results indicate that the model is sensitive to various approaches and can prioritize vulnerable roads comprehensively based on which safety measures can be taken.
- СтавкаAssessment of Conditions for Implementing Information Technology in aWarehouse System: A Novel Fuzzy PIPRECIA Method(MDPI, 2018) Stević, Željko; Stjepanović, Željko; Božičković, Zdravko; Kumar Das, Dillip; Stanujkić, DragišaThe application of information technology in all areas represents a significant facilitation of all business processes and activities. A competitive business system is hardly imaginable without adequate information technology. Therefore, this paper evaluates the conditions for the implementation of barcode technology in a warehouse system of a company for the manufacture of brown paper. SWOT (Strengths,Weaknesses, Opportunities, Threats) matrix was formed with a total of 27 elements based on which the benefits of the implementation of barcode technology in the warehouse system need to be analysed. For this purpose, a new fuzzy PIPRECIA (PIvot Pairwise RElative Criteria Importance Assessment) method has been developed to evaluate all elements in SWOT matrix. In addition, a part of the new developed approach includes new fuzzy scales for criterion assessment that are adapted to the methodology required by the fuzzy PIPRECIA method. To determine the consistency of the method, Spearman and Pearson correlation coefficients are applied. The results obtained in this study show that weaknesses are most noticeable in the current system. By implementing barcode technology, it is possible to create opportunities defined in SWOT matrix, which, in a very efficient way, allow elimination of the current weaknesses of the system
- СтавкаDevelopment of Integrated Linear Programming Fuzzy-Rough MCDM Model for Production Optimization(MDPI, 2022) Dordevic, Milan; Tešić, Rade; Todorović, Srdjan; Jokić, Miloš; Kumar Das, Dillip; Stević, Željko; Vrtagic, SabahudinOne of the most common tools for achieving optimization and adequate production process management is linear programming (LP) in various forms. However, there are specific cases of the application of linear programming when production optimization implies several potential solutions instead of one. Exactly such a problem is solved in this paper, which integrates linear programming and a Multi-Criteria Decision-Making (MCDM) model. First, linear programming was applied to optimize production and several potential solutions lying on the line segment AB were obtained. A list of criteria was created and evaluated using the Improved Fuzzy StepwiseWeight Assessment Ratio Analysis (IMF SWARA). To obtain the final solution, a novel Rough compromise ranking of alternatives from distance to ideal solution (R-CRADIS) method was developed and verified through comparative analysis. The results show that the integration of linear programming and a Fuzzy-Rough MCDM model can be an exceptional solution for solving specific optimization problems.
- СтавкаNovel Extension of DEMATEL Method by Trapezoidal Fuzzy Numbers and D Numbers for Management of Decision-Making Processes(MDPI, 2020) Pribićević, Ivan; Doljanica, Suzana; Momčilović, Oliver; Kumar Das, Dillip; Pamučar, Dragan; Stević, ŽeljkoThe decision-making trial and evaluation laboratory (DEMATEL) method is one of the most significant multi-criteria techniques for defining the relationships among criteria and for defining the weight coe cients of criteria. Since multi-criteria models are very often used in management and decision-making under conditions of uncertainty, the fuzzy DEMATEL model has been extended in this paper by D numbers (fuzzy DEMATEL-D). The aim of this research was to develop a multi-criteria methodology that enables the objective processing of fuzzy linguistic information in the pairwise comparison of criteria. This aim was achieved through the development of the fuzzy DEMATEL-D method. Combining D numbers with trapezoidal fuzzy linguistic variables (LVs) allows for the additional processing of uncertainties and ambiguities that exist in experts’ preferences when comparing criteria with each other. In addition, the fuzzy DEMATEL-D methodology has a unique reasoning algorithm that allows for the rational processing of uncertainties when using fuzzy linguistic expressions for pairwise comparisons of criteria. The fuzzy DEMATEL-D methodology provides an original uncertainty management framework that is rational and concise. In order to illustrate the e ectiveness of the proposed methodology, a case study with the application of the proposed multi-criteria methodology is presented.
- СтавкаObjective Criticism and Negative Conclusions on Using the Fuzzy SWARA Method in Multi-Criteria Decision Making(MDPI, 2022) Stević, Željko; Kumar Das, Dillip; Tešić, Rade; Vidas, Marijo; Vojinović, DraganThe quality of output or decision-making depends on high-quality input data, their adequate evaluation, the application of adequate approaches, and accurate calculation. In this paper, an objective criticism of applying the fuzzy SWARA (step-wise weight assessment ratio analysis) method based on the Chang TFN (triangular fuzzy number) scale is performed. Through research, it has been noticed that a large number of studies use this approach and, as an epilogue, there are wrong decisions based on inconsistent values in relation to the initial assessment of decision-makers (DMs). Seven representative studies (logistics, construction industry, financial performance management, and supply chain) with different parameter structures and decision matrix sizes have been singled out. The main hypothesis has been set, which implies that the application of this approach leads to wrong decisions because the weight values of the criteria are incorrect. A comparative analysis with the improved fuzzy SWARA (IMF SWARA) method has been created and a number of negative conclusions has been reached on using the fuzzy SWARA method and the Chang scale: Primarily, that using such an approach is impossible for two or more criteria to have equal value, that allocating TFN (1,1,1) leads to criteria values that are inconsistent with expert evaluation, that the last-ranked criteria in the fuzzy SWARA method have no influential value on the ranking of alternatives, that there is a great gap between the most significant and last-ranked criteria, and that the most significant criterion has a huge impact on the evaluation of alternative solutions and decision making. As a general conclusion, it is given that this approach is not adequate for application in problems of multicriteria decision making because it produces inadequate management of processes and activities in various spheres.
- СтавкаTrapezoidal Interval Type-2 Fuzzy PIPRECIA-MARCOS Model for Management Efficiency of Traffic Flow on Observed Road Sections(MDPI, 2023) Xu, Wei; Kumar Das, Dillip; Stević, Željko; Subotić, Marko; Alrasheedi, Adel F.; Sun, ShiruRoad infrastructure management is an extremely important task of traffic engineering. For the purpose of efficient management, it is necessary to determine the efficiency of the traffic flow through PAE 85%, AADT and other exploitation parameters on the one hand, and the number of different types of traffic accidents on the other. In this paper, a novel TrIT2F (trapezoidal interval type-2 fuzzy) PIPRECIA (pivot pairwise relative criteria importance assessment)-TrIT2F MARCOS (measurement of alternatives and ranking according to compromise solution) was developed in order to, in a defined set of 14 road segments, identify the most efficient one for data related to light goods vehicles. Through this the aims and contributions of the study can be manifested. The evaluation was carried out on the basis of seven criteria with weights obtained using the TrIT2F PIPRECIA, while the final results were presented through the TrIT2F MARCOS method. To average part of the input data, the Dombi and Bonferroni operators have been applied. The final results of the applied TrIT2F PIPRECIA-TrIT2F MARCOS model show the following ranking of road segments, according to which Vrhovi–Šešlije M-I-103 with a gradient of 1.00 represents the best solution: A5 > A8 > A2 > A1 > A4 > A3 > A6 > A12 > A13 = A14 > A11 > A7 > A9 > A10. In addition, the validation of the obtained results was conducted by changing the values of the four most important criteria and changing the size of the decision matrix. Tests have shown great stability of the developed TrIT2F PIPRECIA-TrIT2F MARCOS model.