GoemansWilliamsonOptimizer#

class GoemansWilliamsonOptimizer(num_cuts, sort_cuts=True, unique_cuts=True, seed=0)[fuente]#

Goemans-Williamson algorithm to approximate the max-cut of a problem. The quadratic program for max-cut is given by:

max sum_{i,j<i} w[i,j]*x[i]*(1-x[j])

Therefore the quadratic term encodes the negative of the adjacency matrix of the graph.

Parámetros:

num_cuts (int) – Number of cuts to generate.
sort_cuts (bool) – True if sort cuts by their values.
unique_cuts (bool) – The solve method returns only unique cuts, thus there may be less cuts than num_cuts.
seed (int) – A seed value for the random number generator.

Methods

get_compatibility_msg(problem)[fuente]#

Checks whether a given problem can be solved with the optimizer implementing this method.

Parámetros:: problem (QuadraticProgram) – The optimization problem to check compatibility.
Devuelve:: Returns the incompatibility message. If the message is empty no issues were found.
Tipo del valor devuelto:: str

is_compatible(problem)#

Checks whether a given problem can be solved with the optimizer implementing this method.

Parámetros:: problem (QuadraticProgram) – The optimization problem to check compatibility.
Devuelve:: Returns True if the problem is compatible, False otherwise.
Tipo del valor devuelto:: bool

static max_cut_value(x, adj_matrix)[fuente]#

Compute the value of a cut from an adjacency matrix and a list of binary values.

Parámetros:

Devuelve:

value of the cut.

Tipo del valor devuelto:

float

solve(problem)[fuente]#

Returns a list of cuts generated according to the Goemans-Williamson algorithm.

Parámetros:: problem (QuadraticProgram) – The quadratic problem that encodes the max-cut problem.
Devuelve:: A list of generated cuts.
Tipo del valor devuelto:: cuts