Methodology

 

In order to make dynamic time tables that can evolve according to situation we have to automate the time table. To make an automated time table we use Genetic Algorithm.  Local Search Procedures are the most common technology used in researches and projects. In this procedure there are few algorithms. Those are Simulated Annealing, Tabu Search and Genetic Algorithm. 

Simulated Annealing

Simulated Annealing is a technique for finding solutions to optimization problems. The process starts by creating a random initial solution. If our problem contains condition that we want to reduce or maximize parameters or other thing, that problem can be solved by Simulated Annealing. This use in hard combinatorial problems like scheduling, the travelling salesman and the quadratic assignment problem. When it comes to time table problem its use as an optimization procedure for solving the school and universities timetabling problems.

Tabu Search

This method could produce or give best possible answer or solution that near to the best possible solution. Tabu Search helps to solve problems in a wide area of fields such as resource planning, telecommunications, VLSI design, financial analysis, scheduling, space planning, energy distribution, molecular engineering, logistics, pattern classification, flexible manufacturing, waste management, mineral exploration, biomedical analysis, environmental conversation and scores of other problems.

Genetic Algorithm

Genetic algorithm is based on Evolutionary Algorithms. Evolutionary Algorithms (EAs) are a class of direct, probabilistic search and optimization algorithms. GA is very problem specific. GAs have a greater capacity than any other search method in finding the largest number of possible solutions and depict the best possible results. GAs demonstrate real-world significance when applied to timetabling problems where a complex set of scheduling constraints and a various collection of individuals exist. It is generally argued that a timetabling GA develops the best possible schedule. Genetic algorithm is used commonly to develop scheduling systems.

When considering all above algorithms we found that Genetic Algorithm is the best solution on making an automated time table. Coding is really is when compared to other algorithms. GA can find a solution in a very less time. Concept is easy to understand.