A new adaptive mutation technique for genetic algorithm

Genetic algorithm is a promising heuristic search algorithm, which searches the solution space for optimal solution using the genetic operations. Mutation is one among the genetic operators that plays a vital role in searching the solution space. This paper proposes a new adaptive mutation technique to improve the performance of genetic algorithm. The proposed technique intends to mutate the genes in such a way that the mutation aids both global and local searching options. This leads to faster convergence rather than the conventional techniques. The comparative results show that the proposed mutation technique exhibits a drastic performance improvement over the conventional static mutation techniques.