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university-timetable

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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).

  • Updated May 17, 2025
  • Python

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.

  • Updated Jul 9, 2026

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