FATGS / 1-minute brief · 3-minute deep dive
Faculty Allocation and Timetable Generation System
FATGS is a timetable generation system designed to organize academic scheduling requirements involving faculty, classes, subjects, rooms, and weekly time slots.
Structured academic scheduling & allocation.
FATGS is an academic timetable generation system designed to organize scheduling requirements involving faculty, classes, subjects, rooms, and weekly time slots.
Model academic master data
Structured representation of faculty profiles, course catalogs, classrooms, and time slots.
Inspect the decision ↗02Enforce scheduling constraints
Deterministic validation rules preventing concurrent instructor overlap and classroom double-booking.
Inspect the decision ↗03Faculty & room allocation logic
Matching qualified instructors to required subject hours while respecting room capacities.
Inspect the decision ↗- Master data inputCourses, faculty, rooms
- Constraint validationDouble-booking checks
- Slot allocationTeaching workload matching
- Timetable matrixClass & faculty output
Output formats support weekly schedule matrices for both student batches and instructors.
Scheduling constraints & verification +
Constraint validation prevents instructor overlap and checks room suitability against batch size. Master data integrity ensures all subject periods are accounted for in the weekly calendar.
- Faculty availability conflict
- Validation logic prevents assigning any instructor to more than one concurrent lecture.
- Classroom capacity and type
- Rooms are matched by required facility type (e.g. laboratory vs. lecture hall) and capacity.
- Weekly credit distribution
- Subject lecture hours are distributed across the academic week to prevent uneven scheduling.
Active academic project focusing on structured scheduling rules, faculty allocation, and timetable output without conflicting assignments.
The starting point
Generating academic timetables requires coordinating faculty assignments, class groups, room suitability, subjects, and scheduling constraints. Without structured data models and automated scheduling rules, conflicts such as instructor overlap or double-booked classrooms easily occur.
FATGS (Faculty Allocation and Timetable Generation System) is designed to organize academic scheduling requirements involving faculty members, classes, subjects, classrooms, and weekly time slots. The system models academic timetable information and applies scheduling rules to produce structured timetable output.
This project focuses on data modeling, constraint definition, and practical scheduling workflows to automate timetable generation while respecting academic requirements.
I designed and implemented the scheduling logic, academic master data model, constraint validation, and timetable generation workflow.
01 / Scheduling Logic · Constraint Validation
The academic scheduling problem.
Prevents faculty double-booking and room overlap while satisfying weekly curriculum requirements.
Generating academic timetables requires coordinating faculty assignments, class groups, room suitability, subjects, and scheduling constraints. The system structures these requirements into defined validation rules before slot assignment.
Academic scheduling involves multiple interdependent variables: teachers have specific subject proficiencies and availability; student batches have required course hours; and rooms have differing capacities and facilities.
Manual timetable drafting often results in subtle conflicts that are difficult to diagnose before the semester begins. FATGS models these relationships explicitly, checking that assignments satisfy course credit distributions across the working week.
The system treats double-booking prevention as an essential hard constraint: at no point can an instructor or a classroom be allocated to two concurrent sessions.
02 / Data Modeling · Schema Design
Structuring academic master data.
Provides a consistent data model for courses, professors, batches, and physical classrooms.
The system models academic timetable information and applies scheduling rules to produce structured timetable output. It supports academic master data, slot information, faculty allocation, and timetable generation workflows.
The academic data model forms the core of FATGS. It defines entities for departments, faculty members, course subjects, student cohorts, lecture rooms, and time slot intervals.
By establishing clean schemas and relational mappings across these master entities, scheduling queries can efficiently inspect slot occupancy and subject requirements.
This master data approach ensures that changes to faculty availability or room allocations can be updated centrally without invalidating the broader scheduling framework.
03 / Faculty Allocation · Slot Assignment
Rules for faculty and room allocation.
Ensures balanced teaching allocations and verifies room suitability for scheduled subjects.
Faculty preferences and subject requirements are matched against available time slots and room capacities. Conflict checks verify that neither an instructor nor a classroom is assigned to concurrent sessions.
Faculty allocation coordinates instructor availability with subject distribution. The system maps teaching loads to prevent individual faculty over-allocation while ensuring all course topics have qualified instructors assigned.
Room suitability matching checks that lab sessions are assigned to appropriate specialized spaces and regular lectures are assigned to classrooms that accommodate the batch size.
Allocation rules process preferences and availability windows, applying deterministic assignment logic to slot faculty into open periods.
04 / Timetable Generation · Output Formatting
Timetable generation and output workflow.
Produces structured weekly timetables organized by class group and faculty schedule.
The workflow processes master records and slot constraints through structured scheduling steps to output complete weekly schedules.
The timetable generation workflow processes the master data and constraint sets sequentially. Unassigned periods are matched against eligible faculty-room combinations until the weekly schedule is filled.
Generated timetables are formatted into both class-wise matrices and faculty-wise views. This allows students to view their cohort's weekly schedule while giving professors a consolidated calendar of their assigned hours.
Output structures support review and export, providing academic administrators with transparent views of weekly slot allocations.
What I take from it.
Building FATGS provided hands-on experience in modeling complex scheduling constraints and designing relational data structures for academic workflows.
The project demonstrates how structured rules and algorithmic planning can simplify administrative coordination in educational institutions.
Active academic project. Focuses on structured scheduling rules, faculty allocation, and timetable output without conflicting assignments.