SlsqpOptimizer¶
-
class
SlsqpOptimizer
(iter=100, acc=1e-06, iprint=0, trials=1, clip=100.0, full_output=False)[source]¶ Bases:
qiskit.optimization.algorithms.multistart_optimizer.MultiStartOptimizer
The SciPy SLSQP optimizer wrapped as an Qiskit
OptimizationAlgorithm
.This class provides a wrapper for
scipy.optimize.fmin_slsqp
(https://docs.scipy.org/doc/scipy-0.13.0/reference/generated/scipy.optimize.fmin_slsqp.html) to be used within the optimization module. The arguments forfmin_slsqp
are passed via the constructor.Examples
>>> from qiskit.optimization.problems import QuadraticProgram >>> from qiskit.optimization.algorithms import SlsqpOptimizer >>> problem = QuadraticProgram() >>> # specify problem here >>> x = problem.continuous_var(name="x") >>> y = problem.continuous_var(name="y") >>> problem.maximize(linear=[2, 0], quadratic=[[-1, 2], [0, -2]]) >>> optimizer = SlsqpOptimizer() >>> result = optimizer.solve(problem)
Initializes the SlsqpOptimizer.
This initializer takes the algorithmic parameters of SLSQP and stores them for later use of
fmin_slsqp
whensolve()
is invoked. This optimizer can be applied to find a (local) optimum for problems consisting of only continuous variables.- Parameters
iter (
int
) – The maximum number of iterations.acc (
float
) – Requested accuracy.iprint (
int
) –The verbosity of fmin_slsqp :
iprint <= 0 : Silent operation
iprint == 1 : Print summary upon completion (default)
iprint >= 2 : Print status of each iterate and summary
trials (
int
) – The number of trials for multi-start method. The first trial is solved with the initial guess of zero. If more than one trial is specified then initial guesses are uniformly drawn from[lowerbound, upperbound]
with potential clipping.clip (
float
) – Clipping parameter for the initial guesses in the multi-start method. If a variable is unbounded then the lower bound and/or upper bound are replaced with the-clip
orclip
values correspondingly for the initial guesses.full_output (
bool
) – IfFalse
, return only the minimizer of func (default). Otherwise, output final objective function and summary information.
Methods
Checks whether a given problem can be solved with this optimizer.
Checks whether a given problem can be solved with the optimizer implementing this method.
Applies a multi start method given a local optimizer.
Tries to solves the given problem using the optimizer.
Attributes
-
clip
¶ Returns the clip value for this optimizer.
- Return type
float
- Returns
The clip value.
-
trials
¶ Returns the number of trials for this optimizer.
- Return type
int
- Returns
The number of trials.