Abstract

The proposed system presents a novel approach of solving University timetabling which is NP-hard problem using Genetic Algorithm. Genetic Algorithm is frequently deployed Meta heuristics algorithm which can be effectively used to difficult combinatorial optimization problems. Although, there has been an extensive research towards this field but majority of the research results are much in its nascent stage. The previous researchers have used various methods like Tabu search, Simulated Annealing, network flow, graph coloring, etc. Genetic Algorithms are effective in solving many such optimization problems. The current work presented uses Genetic Algorithm to design an effective model for scheduling with challenging constraints considerations. The objective of the research is to create a model using Genetic Algorithm to the extent it can be used to generate the acceptable schedule using probabilistic operators like mutation and crossover. The design of the fitness function has considered the hard constraints. The simulation shows the better result in minimum time.

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