Intellectualization of logistic supply chains on the basis of forecasting volumes of cargo transportation

Abstract

Research shows that the accelerated economic movement towards a more intelligent model of development and rapid dissemination of knowledge contributes to the emergence of new modern logistics technologies and approaches to managing global supply chains. The dominant feature of the sustainable development of transport services is the invariant concept of management, the basis of which is the socioecological and economic model. Indicators of the transport sector show a decline in volumes of transportation, but the positive dynamics of growth is demonstrated by the agrarian sector, which produces half of all export volumes and provides one third of the currency revenues of the state.Factors that inhibit the effective functioning of the logistics chain are revealed. In particular, the technological orientation of railways, mainly on route transportation, highlighted the problem of uneven development of ports at ports and railway ports, as well as inconsistencies in grain volumes in Stevedoring companies’ deals with real port facilities. In fact, there is a schedule of seasonal fluctuations in the transportation of cereals, in particular, their absence for 3-4 months per year.The rational model of management and intellectualization of grain supply logistic chain, which takes into account the indicators of artificial neural network forecasting and seasonal grain transportation parameter, is proposed.

Optimization of the Export Structure in Transport Companies: A Case Study

“…One should add that a number of authors have also investigated the impact of transport infrastructure on the macroeconomic indicators of the state, evaluating and forecasting such impacts at macro, meso and micro levels: the main direction of their research was to forecast the volumes of cargo without studying their structure (e.g. Gurnak et al, 2019). In turn, the study of Zhou and Hu (2017) examines the stability of a complex economic system on the example of railways in different parts of China by different stages of the production cycle.…”

Особливості Формування Попиту У Моделюванні Ланцюгів Поставок Зернових Культур

“…У сучасних дослідженнях зарубіжних [7] та вітчизняних [8] науковців зустрічаємо моделювання попиту на основі штучних нейронних мереж (ANN-від англ. artificial neural network).…”

“…Такі науковці як Гурнак В., Волинець Л., Халацька І. [8] здійснили прогнозування транспортування зернових завдяки структурній моделі на основі ANN. Цей метод прогнозування має високі властивості адаптації до змінних вхідних даних шляхом самостійного навчання моделі.…”

“…Величина точності прогнозування руху визначається величиною середньої абсолютної похибки у відсотках, яка становить 5,56% [8]. Враховуючи, що транспортна галузь є досить інертною системою, такого показника достатньо для того, щоб прийняти управлінські рішення.…”

Principle of the assessment of the readiness of motor transport enterprises for economic development based on a two-component methodological approach

“…The negative impact of the ongoing processes has significantly increased the requirements for ensuring the sustainability of supply chains of goods, and the processes of optimizing logistics, mergers and acquisitions of transport companies have intensified in this market. A growing trend is the development of e-commerce, which stimulates the acquisition of control over transport and logistics companies at all levels of the supply chain -manufacturer, warehouse, and sales centers [3][4][5]. Increasing investments in modern technologies of supply chain logistics is considered a tool to improve the quality of transport services, reduce operating costs, and reduce the impact on the environment.…”