BinPacking#

class BinPacking(weights, max_weight, max_number_of_bins=None)[source]#

Optimization application for the “bin packing” [1] problem.

References

Parameters:

weights (List[int]) – A list of the weights of items
max_weight (int) – The maximum bin weight capacity
max_number_of_bins (int | None) – The maximum number of bins by default equal to the number of items

Methods

get_figure(result)[source]#

Get plot of the solution of the Bin Packing Problem.

Parameters:: result (OptimizationResult | ndarray) – The calculated result of the problem
Returns:: A plot of the solution, where x and y represent the bins and sum of the weights respectively.
Return type:: fig

interpret(result)[source]#

Interpret a result as item indices

Parameters:: result (OptimizationResult | ndarray) – The calculated result of the problem
Returns:: A list of lists with the items in each bin
Return type:: items_in_bins

static sample_most_likely(state_vector)#

Compute the most likely binary string from state vector.

Parameters:: state_vector (QuasiDistribution | Statevector | ndarray | Dict) – state vector or counts or quasi-probabilities.
Returns:: binary string as numpy.ndarray of ints.
Raises:: ValueError – if state_vector is not QuasiDistribution, Statevector, np.ndarray, or dict.
Return type:: ndarray

to_quadratic_program()[source]#

Convert a bin packing problem instance into a QuadraticProgram

Returns:: The QuadraticProgram created from the bin packing problem instance.
Return type:: QuadraticProgram