Повышение эффективности функционирования малоинтенсивных линий: постановка задачи и математические модели

Abstract

Purpose: The article proposes a solution of the problem of functioning of low-intensity lines. The provisions of the strategies for the development of railway transport for various planning horizons are considered in the context of improving the efficiency of the operation of low-intensity lines. The mechanism of assessment on the set of indicators and stages of life cycle of the lines has been defined. The scenarios of sustainable development of low-intensity lines depending on life cycle phase are formed. The mechanism for the evaluation and current stimulation of low-intensity lines has been developed to maintain optimal values of key parameters. The features of the functioning of low-intensity lines on Russian railways are determined in terms of high social significance for population and strategic importance for the country and the correlation of the size of traffic in the regions with the country economic development. Mathematical formulation of the problem of effective functioning of low-intensity lines based on its decomposition is proposed to determine the stages of the life cycle. The model of managing the interaction of intense and low-intensity lines has been improved by means of fuzzy cognitive modeling methods. An enlarged fuzzy cognitive map for the control of intense and low-intensity lines is presented. Control concepts that have a significant impact on the control object are defined. Methods: Methods of analysis and synthesis, system theory, mathematical modeling are applied. Results: A solution for the problem of increasing the efficiency of the operation of low-intensity lines in modern conditions from the standpoint of loosely-structured systems is proposed. Practical significance: Mathematical formulation of the problem of low-intensity line functioning is presented which is solved by determining the stages of the life cycle and the model for managing the interaction between intense and low-intensity lines based on fuzzy cognitive modeling for practical application to existing low-intensity lines.