HyGADE: Hybrid of Genetic Algorithm and Differential Evolution Algorithm
Damini Chaudhary, Anil Kumar Tailor, Vishnu Prakash Sharma, Stuti Chaturvedi · 2019
In the area of evolutionary algorithm, Genetic algorithm and Differential evolution algorithms are the most popular algorithms. Both algorithms used to determine different types of optimization problems. One of them is finding a solution which is close to global minima. In this paper, we have suggested a hybrid algorithm of genetic algorithm and differential evolution algorithm. Crossover operator is the main part of the genetic algorithm while a mutation operator is the main part of the differential evolution algorithm. We tried to get the result close with global optimum with this algorithm. In this paper, we used the mutation operator of differential evolution with improved 3-parent crossover of genetic algorithm. We have tested this algorithm on benchmark functions. This algorithm compared with the basic genetic algorithm and DE algorithm and genetic algorithm with modified crossover.