TECHNOLOGICAL DESIGN OF CAR SERVICE STATIONS USING GENETIC ALGORITHMS

Abstract

The study describes the use of evolutionary methods or genetic algorithms for the technological design of newly constructed or modernized car service stations. Genetic algorithms are one of the types of machine learning models and are actively used to solve multifactor optimization problems. A task of this type is to search for the technical parameters of a car service enterprise under which the economic indicators of its activities will correspond to the profit or capital cost restrictions set by the user. The paper presents the parameters of the developed model, fitness functions, and also provides an assessment of the effectiveness of using the method of genetic algorithms relative to the method of simply enumerating different options for combinations of initial factors. Purpose. Increasing the efficiency of management of road transport enterprises by using the method of genetic algorithms for strategic planning tasks. Methodology. The research uses the method of genetic algorithms to solve a multi-criteria reverse optimization problem in the technological design of a car service station Results. The use of the method of genetic algorithms for the design of service stations and enterprises for the maintenance and repair of vehicles is justified, taking into account the restrictions or targets established at the beginning of the design. Practical implications. The results of the research can be used by the management of enterprises for the maintenance and repair of vehicles in their technological design, strategic planning of activities and modernization.

Keywords

• technological design
• cars
• genetic algorithms
• optimization
• service