embcol.optimizers.RandomGlobalOptimizer¶

class embcol.optimizers.RandomGlobalOptimizer(problem, callback=(), cost_tol=1e-08, rng=None)[source]¶

Random global optimizer.

Search a global optimum by the random sampling.

Parameters:

problem (embcol.problem.Problem) – Optimization problem.
callback (callable or sequence of callable, optional) – Function(s) called after each iteration. The signature of a function must be (params, cost, state) -> None, where params is a one-dimensional array of parameters of type numpy.ndarray, cost is a cost value of type float, and state is a dict object of str to float detailing an optimization state.
cost_tol (float, optional) – Convergence tolerance for the cost.
rng (rng-like, optional) – Random number generator. If nothing is given, a generator is initialized nondeterministically.

Inherited methods

optimize([max_n_iters, resume])

Run an optimization.