Expediting the convergence of evolutionary algorithms by identifying promising regions of the search space.
Kamrul Hasan RahiAhsanul HabibHemant Kumar SinghTapabrata RayPublished in: GECCO Companion (2020)
Keyphrases
- evolutionary algorithm
- search space
- fitness function
- population diversity
- differential evolution
- multi objective
- evolutionary search
- optimization problems
- evolutionary computation
- convergence speed
- fitness landscape
- multi objective optimization
- differential evolution algorithm
- metaheuristic
- genetic programming
- evolution strategy
- optimization method
- search algorithm
- global optimum
- heuristic search
- simulated annealing
- genetic algorithm
- multi objective evolutionary algorithms
- search strategy
- reduce the search space
- image regions
- genetic operators
- initial population
- global search
- input image
- evolutionary process
- evolutionary artificial neural networks
- convergence rate
- particle swarm
- mutation operator
- search tree
- image structure
- parameter space
- particle swarm optimization
- bayesian networks
- image sequences