The Problem
Universities, schools and training centres struggle to allocate subjects, teachers, and rooms without conflicts. Manual planning is slow, error-prone, and rarely optimal.
An ADA Mini Project built for real-world scheduling
This application is a demonstration of how classical algorithms — Greedy and Backtracking — can solve the timeless NP-hard problem of academic timetable generation, often referred to as the "graph coloring" challenge of education.
The Solution
A pipeline of 4 algorithmic stages that ingests records, greedily assigns slots, backtracks on conflicts, and balances subject distribution for a fair week.
The Algorithms
Greedy — pick the first valid slot to keep complexity low. Backtracking — when a conflict appears, tear down the last placement and try the next best alternative until a valid schedule emerges.
The Tech
Built as a static, fast-loading web app with a modern SaaS interface. All computation happens client-side in your browser — no servers, no waiting, no data leaving your device.
The 4-Stage Pipeline
1
Data Prep
Subjects, teachers, and classrooms are organized into searchable entities.
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2
Greedy
For each subject, the first slot matching teacher and room availability is chosen.
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3
Backtrack
On any clash, the system rewinds the last assignment and explores alternatives.
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4
Balance
Distribution rules cap the same subject per day for an organized week.