DAA-Project

Title

Comparative Study To Solve Academic Timetable Scheduling Problem

Problem Statement

• The project tries to draw a comparative study between Solving the Academic TimeTable Scheduling Problem using Neural Networks and Genetic Algorithms and analysing the differences, advantages and disadvantages between the two methodologies.

Team Members

• Salman Shah
• Aiman Abdullah
• Jyoti Prakash
• Abhishek S.

Documentation

• Project slides can be found here

Reference Papers to be referred

• Solving the Academic Timetable Problem Thinking on Student Needs (2015 IEEE 14th International Conference on Machine Learning and Applications) - Base Paper
• Solving Timetable Scheduling Problem by Using Genetic Algorithms - Reference Paper 1
• Using a Genetic Algorithm Optimizer Tool To Solve University Timetable Scheduling Problem(Signal Processing and Its Applications, ISSPA 2007.) - Reference Paper 2
• Time-table scheduling using neural network algorithms - Reference Paper 3