Прегледај по Аутор "PRENTKOVSKIS, Olegas"

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    A Novel Multicriteria Approach – Rough Step-Wise Weight Assessment Ratio Analysis Method (R-SWARA) and Its Application in Logistics
    (National Institute for R&D in Informatics, ICI Bucharest, 2018) ZAVADSKAS, Edmundas Kazimieras; Stević, Željko; TANACKOV, Ilija; PRENTKOVSKIS, Olegas
    A decision-making process often requires knowledge of numerous parameters and their interaction in order to make valid decisions that will result in meeting the objectives set. Multi-criteria decision-making is an area that helps in decision-making processes considering a set of criteria and alternatives. A new MCDM approach has been developed in this paper with a view to better managing the uncertainties and the subjectivity of real decision problems. In the last few years, the integration of Rough numbers and multi-criteria decision-making methods has enjoyed a great popularity, so in this paper, the Rough Step-wise Weight Assessment Ratio Analysis (SWARA) approach has been developed. The developed approach has been verified throughout a sensitivity analysis, which involves the comparison of the obtained results with two other methods for determining the weight values, the Rough Best Worst method (BWM) and Rough Analytic Hierarchy Process (AHP). The correlation of obtained ranks using the Rough SWARA approach with the ranks of Rough BWM and Rough AHP is complete, i.e. the ranks are identical, which confirms the stability and credibility of the developed approach
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    A Novel Rough Range of Value Method (R-ROV) for Selecting Automatically Guided Vehicles (AGVs)
    (ICI Bucharest, 2018) ZAVADSKAS, Edmundas Kazimieras; Nunić, Zdravko; STJEPANOVIĆ, Željko; PRENTKOVSKIS, Olegas
    Material Handling Equipment is a set of different tools, devices, applications that aim to facilitate the handling of materials and products. It is used inside the warehouse, but also between warehouses and production facilities. As an important type of material handling equipment, automatically guided vehicles (AGVs) play one of the key roles in warehouse automation. The benefits of applying the AGVs in the warehouse automation process include: reducing labor costs, increasing reliability and productivity, reducing the damage of goods, safety improving, managing and controlling the complete system, etc. In this paper, a Novel Rough Range of Value Method (R-ROV) for evaluating and selecting AGVs in the warehouse has been developed, which is one of the main contributions. In addition, the Full Consistency Method (FUCOM) was used to determine the weight values of the criteria. The model was formed through nine AGVs and 7 criteria. In the framework of checking the stability of the obtained results and the developed model, the comparison was performed using: Rough WASPAS (Weighted Aggregated Sum Product ASsessment), Rough SAW (Simple Additive Weighting) and Rough MABAC (Multi-Attributive Border Approximation area Comparison). Sensitivity analysis showed high correlation of ranks with all the applied methods by employing the Spearman’s Correlation Coefficient (SCC).