A decision-making process requires a prior definition and fulfilment of certain factors, especially when it refers to complex fields such as supply chain management. One of the most important items in the initial stage of a supply chain, which strongly influences its further flow, is making a decision on the most suitable supplier. In this paper, a model for evaluation and supplier selection has been proposed, which has been considered in more than ten different production areas. The model consists of twenty quantitative and qualitative criteria, which are reduced to a total of nine by the application of the fuzzy AHP and the assessment of managers in production companies. The verification of the model has been presented throughout a selection of suppliers in a company for the production of plastic bags and foils, where the Fuzzy Analytic Hierarchy Process (Fuzzy AHP) method has been used to determine the significance of the criteria, and the Fuzzy Evaluation based on Distance from Average Solution (Fuzzy EDAS) to evaluate and select suppliers. The obtained results have been considered throughout a sensitivity analysis in which a total of 15 different scenarios have been formed and where the stability of the model has been determined, since the supplier one is the best solution in all the cases.

Abstract. Th e article describes mathematical models of traffi c fl ows to initiate diff erent traffi c fl ow processes. Separate elements of traffi c fl ow models are made in a way to be connected together to get a single complex model. A model of straight road with diff erent boundary conditions is presented as a separate part of the network traffi c fl ow model. First testing is conducted in case the fi nal point of the whole modelled traffi c line is closed and no output from that point is possible. Th e second test is performed when a constant value of traffi c fl ow speed and traffi c fl ow rate is entered. Mathematical simulation is carried out and the obtained results are listed.

The research of fractographic images of metals is an important method that allows obtaining valuable information about the physical and mechanical properties of a metallic specimen, determining the causes of its fracture, and developing models for optimizing its properties. One of the main lines of research in this case is studying the characteristics of the dimples of viscous detachment, which are formed on the metal surface in the process of its fracture. This paper proposes a method for detecting dimples of viscous detachment on a fractographic image, which is based on using a convolutional neural network. Compared to classical image processing algorithms, the use of the neural network significantly reduces the number of parameters to be adjusted manually. In addition, when being trained, the neural network can reveal a lot more characteristic features that affect the quality of recognition in a positive way. This makes the method more versatile and accurate. We investigated 17 models of convolutional neural networks with different structures and selected the optimal variant in terms of accuracy and speed. The proposed neural network classifies image pixels into two categories: “dimple” and “edge”. A transition from a probabilistic result at the output of the neural network to an unambiguously clear classification is proposed. The results obtained using the neural network were compared to the results obtained using a previously developed algorithm based on a set of filters. It has been found that the results are very similar (more than 90% similarity), but the neural network reveals the necessary features more accurately than the previous method.

Building and, especially, reconstruction and repairs of highways, call for the development of stone materials manufacturing industry. Increasing need for stone materials may be satisfied by a wide use of industrial waste and secondary resources. In road building, slag of ferrous and nonferrous metallurgy is one of the most popular wastes which are increasingly widespread with every year. Such slag is a valuable raw material for preparation of macadam materials and mineral binders serving as a base for asphalt concrete mixtures and manufacturing of cement emulsions, which are widely used in road paving. The research focused on the use of different types of slag in road construction in Ukraine. Possibilities of using crushed rock and sand as recrement slag of different production for preparation of asphalt concrete and cement mixtures to be used for road-base was studied, as well as the use of slag materials for construction of lower category roads. In the given work, the opportunity to recycle electric furnace steel-smelting slag for preparation of asphalt concrete mixtures was defined.

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