scalation.optimization.DifferentialEvolution
The DifferentialEvolution object solves optimization problems using the Differential Evolution algorithm. This population-based metaheuristic optimizes a real-valued function by iteratively improving candidate solutions. minimize f(x)
Attributes
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Supertypes
class Object
trait Matchable
class Any
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Perform Differential Evolution optimization on objective function f.
Perform Differential Evolution optimization on objective function f.
Value parameters
CR
the crossover probability
F
the differential weight (scaling factor)
bounds
the search boundaries as a tuple (min, max)
dim
the dimensionality of the solution space
f
the real-valued objective function to be minimized
maxGen
the maximum number of generations
popSize
the population size (approx. 10 * dim)
Attributes
Returns
a tuple containing the best solution vector and its objective function value
Return the loss function for each epoch.
Return the loss function for each epoch.
Attributes
Inherited from:
MonitorEpochs