ПРИМЕНЕНИЕ ПРАВИЛ НЕЧЕТКОЙ ЛОГИКИ ДЛЯ АНАЛИЗА ДАННЫХ И ПРИНЯТИЯ РЕШЕНИЙ ПРИ УПРАВЛЕНИИ ГРУЗОПЕРЕВОЗКАМИ В УСЛОВИЯХ НЕОПРЕДЕЛЕННОСТИ

Abstract

Today, the transport services market and the transportation market play a leading role among the system-forming basic components of the transport services market. The transformation of a number of production processes, caused by the digitalization of the economy, has not left aside the management of logic. The article deals with the automation of the formation of alternative routes through the use of the developed algorithm (the mathematical support of which is based on the application of the rules of odd logic), which implements the optimization of the choice based on the customer's requests in the organization of cargo transportation. This approach will allow firms not only to manage their work processes in conditions of risk and uncertainty caused by increasing competition and external factors that are difficult to predict, including economic and geopolitical ones, but also to customize orders, while reducing risks using methods of their distribution. The article substantiates the application of this algorithm and provides a description of its implementation within one of the modules of the proposed intelligent decision support system for cargo traffic management. The purpose of the study is to describe and test the mathematical apparatus of the theory of fuzzy sets adapted to the search for cargo transportation routes, which allows automating a number of poorly formalized processes for a decision-maker in the logistics sphere. Materials and methods. Based on the analysis of scientific ideas and methodological approaches in logistics of domestic and foreign authors, as well as mathematical methods and models, the choice of tools for improving the efficiency of cargo transportation organization through automation of management processes was made. Results. The fuzzy logic apparatus has been adapted to solve logistical problems: a selection of criteria is presented, alternative routes are formulated, computational experiments implemented through the Yandex DataLens environment are described. The model was adjusted taking into account the weight coefficients of the criteria based on the customer's wishes. The analysis and synthesis of the obtained results are presented, as well as the advantages of the proposed approach, relative to the traditional ones, are described. The functionality and interface of the automated module of the system was tested with the involvement of a group of experts interested in using the development, which showed its operability and effectiveness of application. Conclusion. The proposed method of choosing alternative routes can be used as a mathematical tool for automating cargo transportation management in decision support systems, especially when planning activities by small firms using their own fleet.