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This project focuses on Adaptive University Timetabling Optimization using a hybrid approach combining Genetic Algorithm (GA) and genetic algorithm variation like memetic and cultural simulated annealing algorithm artificial bee clony ABC algorithm Particle Swarm Optimization (PSO).
A smart timetable assistant for the University of Sargodha computing department. Parse PDF schedules automatically, view class calendars, and check real-time room & lab availability.
A genetic algorithm–based university timetabling system that generates optimized session schedules while satisfying hard constraints and incorporating teacher and student preferences to improve attendance and resource utilization.
A high-performance, local-first mobile app for secure, offline data extraction from complex UOS timetable PDFs—the most challenging aspect of this project. Engineered with Flutter and a native C++ engine via Dart FFI, it ensures zero-upload parsing and strict data privacy.