УДОСКОНАЛЕННЯ МЕТОДУ ПРИЗНАЧЕННЯ ЗАДАЧ ДЛЯ СПІВРОБІТНИКІВ СТАНЦІЇ ТЕХНІЧНОГО ОБСЛУГОВУВАННЯ ТРАНСПОРТНИХ ЗАСОБІВ НА БАЗІ ГЕНЕТИЧНОГО ТА УГОРСЬКОГО АЛГОРИТМІВ

Abstract

The method of automated process of assigning tasks to employees of vehicle service stations based on genetic and Hungarian algorithms has been improved, which, unlike existing ones, takes into account the complexity of the task, the time of task execution and the qualifications of workers, and also allows to speed up and optimize the workflow at vehicle service stations. To evaluate the optimality of solution options, a new criterion is proposed, which, in addition to the qualifications of the worker, the complexity and time of the task, allows taking into account the needs of the enterprise in different seasons. The experimental data of the proposed algorithms were computerized. The initial data for the computer experiment were taken as data on the functioning of a real service station in Vinnytsia with and without the automated application of an improved method of assigning tasks to employees of a vehicle service station based on genetic and Hungarian algorithms. Computer experiments have shown that genetic algorithm work better with a large number of tasks, and the Hungarian algorithm works better with a small number of tasks. On the basis of the proposed improvements and algorithms, a cross-platform automated system for vehicle service station employees has been developed, which, unlike existing ones, provides instant interaction between the system's software modules, thanks to the microservice architecture and takes into account the high load of client requests, due to the horizontal scaling of the servers that host the system software. A special feature of the automated system is that it provides station employees with an automated workplace where they can manage their own tasks and monitor and control their execution, which allows vehicle service station owners to control the entire customer service process and correctly prioritize tasks for their employees.