Development of a Software Solution for Scheduling for Individual Learning Trajectory

This paper deals with the actual problem of creating efficient schedules in various spheres of human activity such as education and transportation. The difficulties in creating optimal schedules are related to a variety of constraints, requirements and constantly changing conditions. The paper discusses the main problems associated with scheduling and proposes approaches and methods to solve them using modern technologies and artificial intelligence techniques. A developed module for integration with an educational institution and a Telegram bot for scheduling classes are presented. The process of generating schedules based on the entered information about students, classes, time and location is described. A genetic algorithm was used to minimize the target function considering all requirements. Plans for further development are presented, including the creation of a website for constraint and requirement selection, the development of a neural network to evaluate the quality of the generated options, and the creation of a mobile version for user-friendliness. Tests of the program on data from Tyumen State University were conducted, showing its potential for efficient schedule creation.