`scipy.optimize._dual_annealing:StrategyChain`

source: /scipy/optimize/_dual_annealing.py :212

Signature

   class     StrategyChain (    acceptance_param    ,    visit_dist    ,    func_wrapper    ,    minimizer_wrapper    ,    rand_gen    ,    energy_state      )

Members

Summary

Class that implements within a Markov chain the strategy for location acceptance and local search decision making.

Parameters

acceptance_param : float: Parameter for acceptance distribution. It is used to control the probability of acceptance. The lower the acceptance parameter, the smaller the probability of acceptance. Default value is -5.0 with a range (-1e4, -5].
visit_dist : VisitingDistribution: Instance of VisitingDistribution class.
func_wrapper : ObjectiveFunWrapper: Instance of ObjectiveFunWrapper class.
minimizer_wrapper: LocalSearchWrapper: Instance of LocalSearchWrapper class.
rand_gen : {None, int, `numpy.random.Generator`,: numpy.random.RandomState}, optional
If seed is None (or np.random), the numpy.random.RandomState singleton is used. If seed is an int, a new RandomState instance is used, seeded with seed. If seed is already a Generator or RandomState instance then that instance is used.
energy_state: EnergyState: Instance of EnergyState class.

Aliases

scipy.optimize._dual_annealing.StrategyChain