An Empirical Analysis of Genetic Algorithm with Different Mutation and Crossover Operators for Solving Sudoku.
D. SrivatsaT. P. V. Krishna TejaIlam PrathyushaG. JeyakumarPublished in: PReMI (1) (2019)
Keyphrases
- crossover operator
- genetic algorithm
- mutation operator
- evolutionary algorithm
- fitness function
- genetic operators
- traveling salesman problem
- genetic algorithm ga
- differential evolution
- hybrid genetic algorithm
- memetic algorithm
- constrained optimization problems
- mutation strategy
- function optimization
- population diversity
- crossover and mutation operators
- combinatorial optimization
- explore the search space
- multidimensional knapsack problem
- multi objective
- premature convergence
- crossover and mutation
- artificial neural networks
- simulated annealing
- evolutionary programming
- optimization method
- mutation probability
- optimization problems
- genetic programming
- metaheuristic
- nsga ii
- multi objective optimization
- evolutionary computation
- population size
- initial population
- genetic search
- tabu search
- constraint handling
- selection operator
- ant colony optimization
- objective function