Прегледај по Аутор "Štilić, Anđelka"

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    A Comprehensive Decision Framework for Selecting Distribution Center Locations: A Hybrid Improved Fuzzy SWARA and Fuzzy CRADIS Approach
    (MDPI, 2023) Puška, Adis; Štilić, Anđelka; Stević, Željko
    The focus of this study is on the significance of location in establishing distribution centers. The key question when selecting a location is regarding which location would contribute the most to the growth of a company’s business through the establishment of distribution centers. To answer this question, we conducted research in the Brˇcko District of BiH in order to determine the best location for a distribution center using expert decision-making based on linguistic values. In order to use these values when selecting locations, a fuzzy set was formed using the IMF SWARA (Improved Fuzzy Stepwise Weight Assessment Ratio Analysis) and fuzzy CRADIS (Compromise Ranking of Alternatives from Distance to the Ideal Solution) methods. The IMF SWARA method was utilized to determine the weights of the criteria, and the fuzzy CRADIS method was employed to rank the locations based on expert ratings. The location for the construction of distribution centers at Bodarište was rated the worst, while the McGowern Base location was rated the best. Based on these findings, the research question was answered, and it was demonstrated that fuzzy methods could be utilized in the selection of distribution center locations. Hence, we recommend that future research be performed on the application of fuzzy methods in the expert selection of potential sites for distribution centers
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    A Fuzzy–Rough MCDM Approach for Selecting Green Suppliers in the Furniture Manufacturing Industry: A Case Study of Eco-Friendly Material Production
    (MDPI, 2023) Chen, Xuemei; Zhou, Bin; Štilić, Anđelka; Stević, Željko; Puška, Adis
    Green supplier selection is always one of the most important challenges in all of supply chain management, especially for production companies. The purpose is to have reliable suppliers which can fulfill all requests and be flexible in any supply chain stage. The aim of this paper is to create an adequate and strong MCDM (multicriteria decision making) model for the evaluation and selection of suppliers in a real environment. The main contribution of this study is proposing a novel fuzzy–rough MCDM model containing extension stepwise weight assessment ratio analysis (SWARA) and additive ratio assessment (ARAS) methods with fuzzy–rough numbers (FRN). The integrated FRN SWARA–FRN ARAS model was implemented in a case study of eco-friendly material production. The FRN SWARA method was used to calculate the weights of 10 green criteria, while using FRN ARAS, 6 suppliers were evaluated. The results of the applied model show that supplier S3 received the highest ranking, followed by supplier S2, while supplier S5 performed the poorest. In order to verify the strengths of the developed fuzzy–rough approach, we created a comparative analysis, sensitivity analysis, and dynamic matrix, which confirm the robustness of our model.
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    Assessing the Banking Sector of Bosnia and Herzegovina: An Analysis of Financial Indicators through the MEREC and MARCOS Methods
    (Sciendo, 2024) Mastilo, Zoran; Štilić, Anđelka; Gligović, Dejan; Puška, Adis
    The banking sector assumes a pivotal role in the economic development of nations. The assessment of financial indicators pertaining to banks holds fundamental importance in the evaluation of bank stability and sustainability. This research employs the MEREC (Method based on the Removal Effects of Criteria) and MARCOS (Measurement of Alternatives and Ranking according to COmpromise Solution) methodologies to delve deeper into the financial landscape of the banking sector in Bosnia and Herzegovina (BiH). Specifically, the objective is to rank banks according to their financial indicators, utilizing financial data from the year 2022. The MEREC method is applied to gauge the significance of financial indicators and ascertain their respective weights, while the MARCOS method is employed to rank banks within BiH based on their financial indicators. The examination of financial indicators within the BiH banking sector, facilitated by the MEREC and MARCOS methodologies, yields a more comprehensive understanding of the sector's present condition. Limitations of this research, which primarily stem from its reliance on available financial data and predefined methodologies, lies within limited consideration for external factors. To provide a broader contextual perspective, the inclusion of additional financial indicators and comparative analyses with banking sectors of other nations would be imperative. The findings of this research reveal that Raiffeisen Bank exhibits the most favourable financial indicators and demonstrates the highest level of efficiency within this context. Consequently, this research offers insights into identifying exemplary banks that can serve as models for enhancing the performance of others.
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    Selection of EVs as Tourist and Logistic Means of Transportation in Bosnia and Herzegovina’s Nature Protected Areas Using Z-Number and Rough Set Modeling
    (Hindawi, 2023) Puška, Adis; Štilić, Anđelka; Božanić, Darko; Ðurić, Aleksandar; Marinkovic, Dragan
    This research focuses on the use of electric vehicles (EVs) to transport visitors and cargo within Bosnia and Herzegovina’s Kozara National Park. Reduced air pollution and the preservation of natural resources are required to help protect this aerial spa. Together with the expert employees of this NP, the EV that would best suit their needs was chosen. &e process of decision-making combines subjective and objective methods. Employees 8rst chose the criteria and alternatives and then weighed their importance. On that occasion, Z-numbers were used to include uncertainty in the decision, because it is not always possible to make decisions with complete certainty. Furthermore, the weight of these criteria was determined using the fuzzy PIPRECIA (PIvot Pairwise Relative Criteria Importance Assessment) method. Range (C1) became the most important criterion, followed by vehicle cost (C2), and the technical speci8cations of these EVs were used to compare them. Because these speci8cations vary, a rough set was used in which the minimum and maximum EV characteristics were taken based on speci8c criteria. To rank the alternatives, the RCRADIS (Rough Compromise Ranking of Alternatives with Distance to Ideal Solution) method was used. According to the research results, the Mercedes eVito Tourer 90kWh is the highest ranked EV and the validation of the results con8rmed these 8ndings. According to the research results, the Mercedes eVito Tourer 90kWh is the highest ranked EV and the validation of the results con8rmed these 8ndings. &e sensitivity analysis revealed that if criterion C1 is not as important, the other EVs are ranked higher. &is research`s methodology has demonstrated Aexibility, therefore it is recommended for use in similar research.