Прегледај по Аутор "Kopić, Miloš"

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    A Novel Multiphase Model for Traffic Safety Evaluation: A Case Study of South Africa
    (Hindawi, 2021) Stević, Željko; Kumar Das, Dillip; Kopić, Miloš
    Identification 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.
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    ANFIS MODEL FOR DETERMININ G THE ECONOMIC ORDER QUANTITY
    (2018) Sremac, Siniša; Tanackov, Ilija; Kopić, Miloš; Radović, Dunja
    The determination of the economic order quantity is important for the rational realization of the logistics process of transport, manipulation and storage in the supply chain. In this paper an expert model for the determination of the economic order quantity has been developed. The model has been developed using the hybrid method of artificial intelligence Adaptive neuro-fuzzy inference systems - ANFIS. It has been used for modeling a complex logistics process in which it is difficult to determine the interdependence of the presented variables applying classical methods. The hybrid method has been applied to take advantages of the individual methods of artificial intelligence: fuzzy logic and neural networks. Experience of an experts and information on the operations of the company for a certain group of items have been used to form the model. Analysis of the validity of the model results was performed on the basis of the average relative error and it has showed that the model imitates the work of the expert in the observed company with great accuracy. Sensitivity analysis has been applied which indicates that the model gives valid results. The proposed model is flexible and can be applied to various types of goods in supply chain management
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    Model for Risk Calculation and Reliability Comparison of Level Crossings
    (MDPI, 2021) Ercegovac, Pamela; Stojić, Gordan; Kopić, Miloš; Stević, Željko; Sinani, Feta; Tanackov, Ilija
    There is not a single country in the world that is so rich that it can remove all level crossings or provide their denivelation in order to absolutely avoid the possibility of accidents at the intersections of railways and road traffic. In the Republic of Serbia alone, the largest number of accidents occur at passive crossings, which make up three-quarters of the total number of crossings. Therefore, it is necessary to constantly find solutions to the problem of priorities when choosing level crossings where it is necessary to raise the level of security, primarily by analyzing the risk and reliability at all level crossings. This paper presents a model that enables this. The calculation of the maximal risk of a level crossing is achieved under the conditions of generating the maximum entropy in the virtual operating mode. The basis of the model is a heterogeneous queuing system. Maximum entropy is based on the mandatory application of an exponential distribution. The system is Markovian and is solved by a standard analytical concept. The basic input parameters for the calculation of the maximal risk are the geometric characteristics of the level crossing and the intensities and structure of the flows of road and railway vehicles. The real risk is based on statistical records of accidents and flow intensities. The exact reliability of the level crossing is calculated from the ratio of real and maximal risk, which enables their further comparison in order to raise the level of safety, and that is the basic idea of this paper.
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    Neuro-fuzzy inference systems approach to decision support system for economic order quantity
    (Taylor & Francis, 2019) Sremac, Siniša; Zavadskas, Edmundas Kazimieras; Matić, Bojan; Kopić, Miloš; Stević, Željko
    Supply chain management (SCM) has a dynamic structure involving the constant flow of information, product, and funds among different participants. SCM is a complex process and most often characterized by uncertainty. Many values are stochastic and cannot be precisely determined and described by classical mathematical methods. Therefore, in solving real and complex problems individual methods of artificial intelligence are increasingly used, or their combination in the form of hybrid methods. This paper has proposed the decision support system for determining economic order quantity and order implementation based on Adaptive neuro-fuzzy inference systems - ANFIS. A combination of two concepts of artificial intelligence in the form of hybrid neurofuzzy method has been applied into the decision support system in order to exploit the individual advantages of both methods. This method can deal with complexity and uncertainty in SCM better than classical methods because they it stems from experts’ opinions. The proposed decision support system showed good results for determining the amount of economic order and it is presented as a successful tool for planning in SCM. Sensitivity analysis has been applied, which indicates that the decision support system gives valid results. The proposed system is flexible and can be applied to various types of goods in SCM.