smac.acquisition.maximizer.differential_evolution

Classes

DifferentialEvolution(configspace[, ...])

Get candidate solutions via DifferentialEvolutionSolvers from scipy.

Interfaces

class smac.acquisition.maximizer.differential_evolution.DifferentialEvolution(configspace, acquisition_function=None, challengers=5000, seed=0)

Bases: AbstractAcquisitionMaximizer

Get candidate solutions via DifferentialEvolutionSolvers from scipy.

According to scipy 1.9.2 documentation:

‘Finds the global minimum of a multivariate function. Differential Evolution is stochastic in nature (does not use gradient methods) to find the minimum, and can search large areas of candidate space, but often requires larger numbers of function evaluations than conventional gradient-based techniques. The algorithm is due to Storn and Price [1].’

[1] Storn, R and Price, K, Differential Evolution - a Simple and Efficient Heuristic for Global

Optimization over Continuous Spaces, Journal of Global Optimization, 1997, 11, 341 - 359.

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