Прегледај по Аутор "Tadić, Snežana"

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    A Novel Hybrid Model for the Evaluation of Industry 4.0 Technologies’ Applicability in Logistics Centers
    (Hindawi, 2023) Miškić, Smiljka; Tadić, Snežana; Stević, Željko; Krstić, Mladen; Roso, Violeta
    The application of Industry 4.0 (I4.0) in the field of logistics leads to the emergence and development of the concept of logistics 4.0. Many I4.0 technologies have been applied in the field of logistics. The goal of this research is to analyze the applicability of nine key I4.0 technologies in logistics centers (LC). For this purpose, an integrated MEREC (MEthod based on the Removal Effects of Criteria)—fuzzy MARCOS (Measurement of Alternatives and Ranking according to COmpromise Solution) model was developed. The applicability of nine I4.0 technologies was evaluated based on 15 subcriteria within three main groups of criteria, namely, technological, social and political, and economic and operative. Using the MEREC method, the weight values of the criteria and subcriteria were determined, while the technologies were ranked using the fuzzy MARCOS method. Based on the results obtained by applying this integrated MCDM (multicriteria decision-making) model, CC was identified as the best alternative, i.e., the technology that is most applicable in logistics centers, followed by IoT and big data. An analysis of the sensitivity of the obtained results to the change in the importance of the criteria was carried out, which shows certain changes in the ranking when the importance of the most important criterion changes.
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    Assessment of the LPI of the EU countries using MCDM model with an emphasis on the importance of criteria
    (Inderscience Enterprises Ltd, 2023) Miškić, Smiljka; Stević, Željko; Tadić, Snežana; Alkhayyat, Ahmed; Krstić, Mladen
    The World Bank calculates the Logistics Performance Index (LPI) to determine the quality of the logistics system in 160 countries. The LPI analyses differences between countries in six dimensions. When calculating the LPI, the World Bank considers these six dimensions with equal importance. This paper aims to develop an integrated evaluation model of the logistics performance index of European Union (EU) countries with an emphasis on sensitivity analysis, which implies a change in the importance of criteria. By applying the MEREC (MEthod based on the Removal Effects of Criteria) method, the weight values of the six criteria were calculated. By applying the MARCOS (Measurement of alternatives and ranking according to COmpromise solution) method, 27 member states of the European Union (EU) were ranked. According to the integrated model results, Germany is the bestranked country according to the logistics performance index. The sensitivity analysis shows that the weight values of the observed criteria affect the ranking results of the EU countries. Therefore, it is necessary to modify the evaluation of LPI, taking into account the importance of the criteria, and considering the real needs of the countries.
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    Locating Collection and Delivery Points Using the p-Median Location Problem
    (MDPI, 2023) Tadić, Snežana; Krstić, Mladen; Stević, Željko; Veljović, Miloš
    Background: Possible solutions to overcome the many challenges of home delivery are collection and delivery points (CDPs). In addition to commercial facilities, the role of CDPs can also be played by users’ households, providing a crowd storage service. Key decisions regarding CDPs relate to their location, as well as the allocation of users to selected locations, so that the distance of users from CDPs is minimal. Methods: In this paper, the described problem is defined as a p-median problem and solved for the area of the city of Belgrade, using the heuristic “greedy” and the simulated annealing algorithm. Results: Fifty locations of CDPs were selected and the users allocated to them were distributed in over 950 zones. The individual distances between users and the nearest CDPs and the sum of these distances, multiplied by the number of requests, were obtained. An example of modification of the number of CDPs is presented as a way of obtaining solutions that correspond to different preferences of operators and/or users in terms of their distances from the CDPs. Conclusions: User households can be used as CDPs to achieve various benefits. Locating CDPs, i.e., selecting households, can be solved as a p-median problem, using a combination of heuristic and metaheuristic algorithms. In addition, by modifying the number of medians, the total and average distances between users and CDPs can be better managed. The main contributions of the paper are the establishment of users’ households as potential locations of CDPs, the establishment of a framework for analysis of impact of the number of CDPs on the sum and average distances from the customers, as well as the creation of a basis for upgrading and modifying the model for implementation in the business practice.