Systém pro podporu plánování rozvrhů

Abstract

This bachelor thesis focuses on the design and implementation of a web-based system for efficient university course timetabling. The timetabling problem (UCTP) is categorized as an NP-complete task, which precludes finding optimal solutions in real-time using conventional deterministic algorithms. The core of the proposed solution is a genetic algorithm that automates the process of generating feasible and high-quality schedules based on specified hard and soft constraints.

The main contribution of this work is a hybrid interaction model that combines the power of evolutionary optimization with an intuitive manual editor. Built on Django and Vue.js frameworks, the implemented application allows schedulers to actively participate in the process via a drag-and-drop interface, while the system provides real-time data integrity validation and tracks course capacity limits. By utilizing asynchronous processing and WebSocket communication, the application offers a responsive environment for multi-user collaboration. The result is a functional tool that significantly reduces the cognitive load on schedulers and minimizes the risk of human error.