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Found 3 papers, 1 papers with code
Improving TSP Solutions Using GA with a New Hybrid Mutation Based on Knowledge and Randomness
The mutation operator is one of the key success factors in GA, as it is considered the exploration operator of GA.
On Enhancing Genetic Algorithms Using New Crossovers
Novel crossover operators are proposed such as the Collision crossover, which is based on the physical rules of elastic collision, in addition to proposing two selection strategies for the crossover operators, one of which is based on selecting the best crossover operator and the other randomly selects any operator.
Enhancing Genetic Algorithms using Multi Mutations
Mutation is one of the most important stages of the genetic algorithm because of its impact on the exploration of global optima, and to overcome premature convergence.
