The article discusses a way to automate the organization of the work of the support service for users of automated control systems (ACS) of transport enterprises. In the context of digitalization, constant improvement, expanding the functionality of such automated control systems, and an increase in the number of their users, the urgency of the problem is beyond doubt. The work of the support service for users of the automated control system of transport enterprises is presented as a queuing system. The possibility of using various methods to solve the problem is analyzed. A description of the work of the support service, methods of forming its departments are given. The incidents she deals with are classifi ed. An algorithm for the formation of support service departments has been developed. It is proposed to solve this problem using a genetic algorithm. The algorithm and the concepts that characterize it are adapted to achieve the goal stated in the article. Crossover variants are presented that can be used by the genetic algorithm to solve various classes of problems. With the help of the developed software, modeling of the organization of the work of the support service was carried out using the algorithm for the distribution of employees. A comparative analysis of the results of modeling the work of departments with various methods of their formation, including those obtained using a genetic algorithm, has been carried out. The analysis showed the eff ectiveness of the use of the genetic algorithm when planning the work of the relevant departments. The possibility of adapting the developed algorithm for planning the work of personnel involved in the technical maintenance of the infrastructure of urban rail transport systems has been demonstrated. This task is similar to that considered in this article, since in many cases it becomes necessary or possible to use employees with diff erent competencies to perform only one type of work.
work planning, support service, incident handling, automated control system, information system,
genetic algorithm, crossing over, transport system